new-sat

2 x Intel Xeon Platinum 8490H testing with a Quanta Cloud S6Q-MB-MPS (3A10.uh BIOS) and ASPEED on Ubuntu 23.10 via the Phoronix Test Suite.

Compare your own system(s) to this result file with the Phoronix Test Suite by running the command: phoronix-test-suite benchmark 2311059-NE-NEWSAT27963
Jump To Table - Results

View

Do Not Show Noisy Results
Do Not Show Results With Incomplete Data
Do Not Show Results With Little Change/Spread
List Notable Results

Limit displaying results to tests within:

C++ Boost Tests 2 Tests
CPU Massive 2 Tests
Creator Workloads 2 Tests
Fortran Tests 2 Tests
HPC - High Performance Computing 3 Tests
Multi-Core 4 Tests
Intel oneAPI 2 Tests
OpenMPI Tests 3 Tests
Programmer / Developer System Benchmarks 2 Tests
Python Tests 3 Tests
Scientific Computing 2 Tests

Statistics

Show Overall Harmonic Mean(s)
Show Overall Geometric Mean
Show Geometric Means Per-Suite/Category
Show Wins / Losses Counts (Pie Chart)
Normalize Results
Remove Outliers Before Calculating Averages

Graph Settings

Force Line Graphs Where Applicable
Convert To Scalar Where Applicable
Prefer Vertical Bar Graphs

Additional Graphs

Show Perf Per Core/Thread Calculation Graphs Where Applicable

Multi-Way Comparison

Condense Multi-Option Tests Into Single Result Graphs

Table

Show Detailed System Result Table

Run Management

Highlight
Result
Hide
Result
Result
Identifier
Performance Per
Dollar
Date
Run
  Test
  Duration
a
October 28 2023
  1 Hour, 15 Minutes
b
October 28 2023
  49 Minutes
c
October 29 2023
  6 Minutes
d
October 29 2023
  2 Hours, 26 Minutes
e
November 01 2023
  1 Hour, 17 Minutes
f
November 01 2023
  24 Minutes
g
November 02 2023
  1 Hour, 15 Minutes
h
November 02 2023
  1 Hour, 15 Minutes
i
November 02 2023
  1 Minute
j
November 02 2023
  1 Hour, 43 Minutes
k
November 02 2023
  1 Hour, 49 Minutes
l
November 05 2023
  1 Hour, 30 Minutes
m
November 05 2023
  1 Hour, 30 Minutes
n
November 06 2023
  2 Hours, 8 Minutes
Invert Hiding All Results Option
  1 Hour, 15 Minutes

Only show results where is faster than
Only show results matching title/arguments (delimit multiple options with a comma):
Do not show results matching title/arguments (delimit multiple options with a comma):


new-sat 2 x Intel Xeon Platinum 8490H testing with a Quanta Cloud S6Q-MB-MPS (3A10.uh BIOS) and ASPEED on Ubuntu 23.10 via the Phoronix Test Suite. a: Processor: 2 x Intel Xeon Platinum 8490H @ 3.50GHz (120 Cores / 240 Threads), Motherboard: Quanta Cloud S6Q-MB-MPS (3A10.uh BIOS), Chipset: Intel Device 1bce, Memory: 1008GB, Disk: 3201GB Micron_7450_MTFDKCC3T2TFS, Graphics: ASPEED, Network: 2 x Intel X710 for 10GBASE-T OS: Ubuntu 23.10, Kernel: 6.6.0-rc5-phx-patched (x86_64), Desktop: GNOME Shell 45.0, Display Server: X Server 1.21.1.7, Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 1920x1200 b: Processor: 2 x Intel Xeon Platinum 8490H @ 3.50GHz (120 Cores / 240 Threads), Motherboard: Quanta Cloud S6Q-MB-MPS (3A10.uh BIOS), Chipset: Intel Device 1bce, Memory: 1008GB, Disk: 3201GB Micron_7450_MTFDKCC3T2TFS, Graphics: ASPEED, Network: 2 x Intel X710 for 10GBASE-T OS: Ubuntu 23.10, Kernel: 6.6.0-rc5-phx-patched (x86_64), Desktop: GNOME Shell 45.0, Display Server: X Server 1.21.1.7, Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 1920x1200 c: Processor: 2 x Intel Xeon Platinum 8490H @ 3.50GHz (120 Cores / 240 Threads), Motherboard: Quanta Cloud S6Q-MB-MPS (3A10.uh BIOS), Chipset: Intel Device 1bce, Memory: 1008GB, Disk: 3201GB Micron_7450_MTFDKCC3T2TFS, Graphics: ASPEED, Network: 2 x Intel X710 for 10GBASE-T OS: Ubuntu 23.10, Kernel: 6.6.0-rc5-phx-patched (x86_64), Desktop: GNOME Shell 45.0, Display Server: X Server 1.21.1.7, Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 1920x1200 d: Processor: 2 x Intel Xeon Platinum 8490H @ 3.50GHz (120 Cores / 240 Threads), Motherboard: Quanta Cloud S6Q-MB-MPS (3A10.uh BIOS), Chipset: Intel Device 1bce, Memory: 1008GB, Disk: 3201GB Micron_7450_MTFDKCC3T2TFS, Graphics: ASPEED, Network: 2 x Intel X710 for 10GBASE-T OS: Ubuntu 23.10, Kernel: 6.6.0-rc5-phx-patched (x86_64), Desktop: GNOME Shell 45.0, Display Server: X Server 1.21.1.7, Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 1920x1200 e: Processor: Intel Xeon Platinum 8490H @ 3.50GHz (60 Cores / 120 Threads), Motherboard: Quanta Cloud S6Q-MB-MPS (3A10.uh BIOS), Chipset: Intel Device 1bce, Memory: 512GB, Disk: 3201GB Micron_7450_MTFDKCC3T2TFS, Graphics: ASPEED OS: Ubuntu 23.10, Kernel: 6.6.0-rc5-phx-patched (x86_64), Desktop: GNOME Shell 45.0, Display Server: X Server 1.21.1.7, Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 1920x1200 f: Processor: Intel Xeon Platinum 8490H @ 3.50GHz (60 Cores / 120 Threads), Motherboard: Quanta Cloud S6Q-MB-MPS (3A10.uh BIOS), Chipset: Intel Device 1bce, Memory: 512GB, Disk: 3201GB Micron_7450_MTFDKCC3T2TFS, Graphics: ASPEED OS: Ubuntu 23.10, Kernel: 6.6.0-rc5-phx-patched (x86_64), Desktop: GNOME Shell 45.0, Display Server: X Server 1.21.1.7, Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 1920x1200 g: Processor: Intel Xeon Max 9468 @ 3.50GHz (48 Cores / 96 Threads), Motherboard: Quanta Cloud S6Q-MB-MPS (3A10.uh BIOS), Chipset: Intel Device 1bce, Memory: 512GB, Disk: 3201GB Micron_7450_MTFDKCC3T2TFS, Graphics: ASPEED OS: Ubuntu 23.10, Kernel: 6.6.0-rc5-phx-patched (x86_64), Desktop: GNOME Shell 45.0, Display Server: X Server 1.21.1.7, Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 1920x1200 h: Processor: Intel Xeon Max 9468 @ 3.50GHz (48 Cores / 96 Threads), Motherboard: Quanta Cloud S6Q-MB-MPS (3A10.uh BIOS), Chipset: Intel Device 1bce, Memory: 512GB, Disk: 3201GB Micron_7450_MTFDKCC3T2TFS, Graphics: ASPEED OS: Ubuntu 23.10, Kernel: 6.6.0-rc5-phx-patched (x86_64), Desktop: GNOME Shell 45.0, Display Server: X Server 1.21.1.7, Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 1920x1200 i: Processor: Intel Xeon Max 9468 @ 3.50GHz (48 Cores / 96 Threads), Motherboard: Quanta Cloud S6Q-MB-MPS (3A10.uh BIOS), Chipset: Intel Device 1bce, Memory: 512GB, Disk: 3201GB Micron_7450_MTFDKCC3T2TFS, Graphics: ASPEED OS: Ubuntu 23.10, Kernel: 6.6.0-rc5-phx-patched (x86_64), Desktop: GNOME Shell 45.0, Display Server: X Server 1.21.1.7, Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 1920x1200 j: Processor: 2 x Intel Xeon Max 9468 @ 3.50GHz (96 Cores / 192 Threads), Motherboard: Quanta Cloud S6Q-MB-MPS (3A10.uh BIOS), Chipset: Intel Device 1bce, Memory: 1008GB, Disk: 3201GB Micron_7450_MTFDKCC3T2TFS, Graphics: ASPEED, Network: 2 x Intel X710 for 10GBASE-T OS: Ubuntu 23.10, Kernel: 6.6.0-rc5-phx-patched (x86_64), Desktop: GNOME Shell 45.0, Display Server: X Server 1.21.1.7, Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 1920x1200 k: Processor: 2 x Intel Xeon Max 9468 @ 3.50GHz (96 Cores / 192 Threads), Motherboard: Quanta Cloud S6Q-MB-MPS (3A10.uh BIOS), Chipset: Intel Device 1bce, Memory: 1008GB, Disk: 3201GB Micron_7450_MTFDKCC3T2TFS, Graphics: ASPEED, Network: 2 x Intel X710 for 10GBASE-T OS: Ubuntu 23.10, Kernel: 6.6.0-rc5-phx-patched (x86_64), Desktop: GNOME Shell 45.0, Display Server: X Server 1.21.1.7, Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 1920x1200 l: Processor: 2 x Intel Xeon Platinum 8490H @ 3.50GHz (120 Cores / 240 Threads), Motherboard: Quanta Cloud S6Q-MB-MPS (3A10.uh BIOS), Chipset: Intel Device 1bce, Memory: 1008GB, Disk: 3201GB Micron_7450_MTFDKCC3T2TFS, Graphics: ASPEED, Network: 2 x Intel X710 for 10GBASE-T OS: Ubuntu 23.10, Kernel: 6.6.0-rc5-phx-patched (x86_64), Desktop: GNOME Shell 45.0, Display Server: X Server 1.21.1.7, Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 1920x1200 m: Processor: 2 x Intel Xeon Platinum 8490H @ 3.50GHz (120 Cores / 240 Threads), Motherboard: Quanta Cloud S6Q-MB-MPS (3A10.uh BIOS), Chipset: Intel Device 1bce, Memory: 1008GB, Disk: 3201GB Micron_7450_MTFDKCC3T2TFS, Graphics: ASPEED, Network: 2 x Intel X710 for 10GBASE-T OS: Ubuntu 23.10, Kernel: 6.6.0-rc5-phx-patched (x86_64), Desktop: GNOME Shell 45.0, Display Server: X Server 1.21.1.7, Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 1920x1200 n: Processor: 2 x Intel Xeon Platinum 8490H @ 3.50GHz (120 Cores / 240 Threads), Motherboard: Quanta Cloud S6Q-MB-MPS (3A10.uh BIOS), Chipset: Intel Device 1bce, Memory: 1008GB, Disk: 3201GB Micron_7450_MTFDKCC3T2TFS, Graphics: ASPEED, Network: 2 x Intel X710 for 10GBASE-T OS: Ubuntu 23.10, Kernel: 6.6.0-rc5-phx-patched (x86_64), Desktop: GNOME Shell 45.0, Display Server: X Server 1.21.1.7, Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 1920x1200 C-Blosc 2.11 Test: blosclz shuffle - Buffer Size: 8MB MB/s > Higher Is Better l . 14338.2 |================================================================== m . 14241.2 |================================================================== n . 14082.4 |================================================================= C-Blosc 2.11 Test: blosclz shuffle - Buffer Size: 16MB MB/s > Higher Is Better l . 16680.2 |================================================================== m . 16762.6 |================================================================== n . 16392.9 |================================================================= C-Blosc 2.11 Test: blosclz shuffle - Buffer Size: 32MB MB/s > Higher Is Better l . 16111.4 |================================================================== m . 16050.9 |================================================================== n . 15827.9 |================================================================= C-Blosc 2.11 Test: blosclz shuffle - Buffer Size: 64MB MB/s > Higher Is Better l . 12239.3 |================================================================== m . 12161.8 |================================================================== n . 12008.0 |================================================================= C-Blosc 2.11 Test: blosclz noshuffle - Buffer Size: 8MB MB/s > Higher Is Better l . 12794.5 |================================================================== m . 12855.3 |================================================================== n . 12742.3 |================================================================= C-Blosc 2.11 Test: blosclz shuffle - Buffer Size: 128MB MB/s > Higher Is Better l . 8707.4 |=================================================================== m . 8640.0 |================================================================== n . 8564.3 |================================================================== C-Blosc 2.11 Test: blosclz shuffle - Buffer Size: 256MB MB/s > Higher Is Better l . 5519.3 |================================================================== m . 5580.3 |=================================================================== n . 5520.6 |================================================================== C-Blosc 2.11 Test: blosclz bitshuffle - Buffer Size: 8MB MB/s > Higher Is Better l . 14873.2 |================================================================== m . 14846.5 |================================================================== n . 14815.4 |================================================================== C-Blosc 2.11 Test: blosclz noshuffle - Buffer Size: 16MB MB/s > Higher Is Better l . 15231.9 |================================================================== m . 15269.2 |================================================================== n . 15041.6 |================================================================= C-Blosc 2.11 Test: blosclz noshuffle - Buffer Size: 32MB MB/s > Higher Is Better l . 14712.6 |================================================================== m . 14746.7 |================================================================== n . 14569.9 |================================================================= C-Blosc 2.11 Test: blosclz noshuffle - Buffer Size: 64MB MB/s > Higher Is Better l . 11321.9 |================================================================== m . 11315.0 |================================================================== n . 11238.1 |================================================================== C-Blosc 2.11 Test: blosclz bitshuffle - Buffer Size: 16MB MB/s > Higher Is Better l . 16895.0 |================================================================== m . 16810.4 |================================================================== n . 16633.4 |================================================================= C-Blosc 2.11 Test: blosclz bitshuffle - Buffer Size: 32MB MB/s > Higher Is Better l . 15811.9 |================================================================== m . 15827.9 |================================================================== n . 15691.0 |================================================================= C-Blosc 2.11 Test: blosclz bitshuffle - Buffer Size: 64MB MB/s > Higher Is Better l . 11927.7 |================================================================== m . 11905.5 |================================================================== n . 11839.7 |================================================================== C-Blosc 2.11 Test: blosclz noshuffle - Buffer Size: 128MB MB/s > Higher Is Better l . 8089.4 |=================================================================== m . 8059.2 |=================================================================== n . 7960.2 |================================================================== C-Blosc 2.11 Test: blosclz noshuffle - Buffer Size: 256MB MB/s > Higher Is Better l . 5409.4 |=================================================================== m . 5333.4 |================================================================== n . 5324.3 |================================================================== C-Blosc 2.11 Test: blosclz bitshuffle - Buffer Size: 128MB MB/s > Higher Is Better l . 8697.6 |================================================================== m . 8864.5 |=================================================================== n . 8289.6 |=============================================================== C-Blosc 2.11 Test: blosclz bitshuffle - Buffer Size: 256MB MB/s > Higher Is Better l . 5615.4 |=================================================================== m . 5389.3 |================================================================ n . 5455.4 |================================================================= CloverLeaf 1.3 Input: clover_bm Seconds < Lower Is Better a . 14.03 |============ b . 13.69 |============ c . 14.05 |============ d . 19.28 |================= e . 8.74 |======== f . 8.68 |======= g . 10.00 |========= h . 9.87 |========= i . 9.94 |========= j . 78.70 |==================================================================== k . 63.32 |======================================================= n . 14.07 |============ CloverLeaf 1.3 Input: clover_bm16 Seconds < Lower Is Better a . 224.98 |======== b . 214.08 |======== c . 218.67 |======== d . 303.86 |=========== e . 323.53 |============ f . 323.38 |============ g . 183.71 |======= h . 182.63 |======= j . 1584.37 |========================================================== k . 1812.17 |================================================================== n . 222.01 |======== CloverLeaf 1.3 Input: clover_bm64_short Seconds < Lower Is Better a . 24.34 |============== b . 24.97 |============== c . 24.12 |============== d . 32.19 |================== e . 38.96 |====================== f . 38.94 |====================== g . 20.86 |============ h . 20.99 |============ j . 117.20 |=================================================================== k . 73.01 |========================================== n . 24.90 |============== Cpuminer-Opt 23.5 Algorithm: Magi kH/s > Higher Is Better a . 2683.56 |================================================================== b . 2681.44 |================================================================== d . 2672.68 |================================================================= e . 1370.86 |================================== g . 968.45 |======================== h . 986.33 |======================== j . 1946.40 |================================================ k . 1946.34 |================================================ n . 2694.61 |================================================================== Cpuminer-Opt 23.5 Algorithm: scrypt kH/s > Higher Is Better a . 1220.91 |================================================================== b . 1194.30 |================================================================= d . 1189.10 |================================================================ e . 618.59 |================================= g . 472.76 |========================== h . 456.46 |========================= j . 939.58 |=================================================== k . 900.68 |================================================= n . 1201.63 |================================================================= Cpuminer-Opt 23.5 Algorithm: Deepcoin kH/s > Higher Is Better a . 32300 |==================================================================== b . 32320 |==================================================================== d . 32317 |==================================================================== e . 16340 |================================== g . 11730 |========================= h . 12140 |========================= j . 23390 |================================================= k . 23850 |================================================== n . 32400 |==================================================================== Cpuminer-Opt 23.5 Algorithm: Ringcoin kH/s > Higher Is Better a . 5799.03 |======================== b . 5933.75 |======================== d . 5770.26 |======================== e . 5867.89 |======================== g . 5205.00 |===================== h . 5300.21 |====================== j . 15560.00 |================================================================ k . 15770.00 |================================================================= n . 7748.29 |================================ Cpuminer-Opt 23.5 Algorithm: Blake-2 S kH/s > Higher Is Better a . 535240 |=================================================================== b . 535430 |=================================================================== d . 533880 |=================================================================== e . 267760 |================================== g . 191940 |======================== h . 191940 |======================== j . 382680 |================================================ k . 382610 |================================================ n . 534840 |=================================================================== Cpuminer-Opt 23.5 Algorithm: Garlicoin kH/s > Higher Is Better a . 3725.51 |========= b . 3727.55 |========= d . 4200.71 |=========== e . 11540.00 |============================= g . 2256.38 |====== h . 2332.32 |====== j . 20460.00 |=================================================== k . 20550.00 |=================================================== n . 26000.00 |================================================================= Cpuminer-Opt 23.5 Algorithm: Skeincoin kH/s > Higher Is Better a . 133860 |=================================================================== b . 133600 |=================================================================== d . 134140 |=================================================================== e . 67000 |================================= g . 50420 |========================= h . 48010 |======================== j . 95670 |================================================ k . 95990 |================================================ n . 133840 |=================================================================== Cpuminer-Opt 23.5 Algorithm: Myriad-Groestl kH/s > Higher Is Better a . 47950 |==================================================================== b . 46280 |================================================================== d . 47623 |==================================================================== e . 25310 |==================================== g . 17860 |========================= h . 18010 |========================== j . 35700 |=================================================== k . 35610 |=================================================== n . 46430 |================================================================== Cpuminer-Opt 23.5 Algorithm: LBC, LBRY Credits kH/s > Higher Is Better a . 58960 |=================================================================== b . 59690 |==================================================================== d . 58620 |=================================================================== e . 29550 |================================== g . 21190 |======================== h . 21180 |======================== j . 42230 |================================================ k . 42230 |================================================ n . 59060 |=================================================================== Cpuminer-Opt 23.5 Algorithm: Quad SHA-256, Pyrite kH/s > Higher Is Better a . 267960 |================================================================== b . 269860 |=================================================================== d . 267450 |================================================================== e . 136700 |================================== g . 97890 |======================== h . 97960 |======================== j . 195710 |================================================ k . 196100 |================================================ n . 271570 |=================================================================== Cpuminer-Opt 23.5 Algorithm: Triple SHA-256, Onecoin kH/s > Higher Is Better a . 384930 |=================================================================== b . 384820 |=================================================================== d . 384423 |=================================================================== e . 194980 |================================== g . 139540 |======================== h . 140170 |======================== j . 278140 |================================================ k . 278150 |================================================ n . 385290 |=================================================================== DuckDB 0.9.1 Benchmark: IMDB Seconds < Lower Is Better a . 259.42 |=================================================================== d . 259.28 |=================================================================== DuckDB 0.9.1 Benchmark: TPC-H Parquet Seconds < Lower Is Better a . 178.04 |=================================================================== d . 178.83 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: FFTW - Precision: float - X Y Z: 128 GFLOP/s > Higher Is Better a . 140.10 |================================================================= b . 145.30 |=================================================================== c . 144.14 |================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: FFTW - Precision: float - X Y Z: 256 GFLOP/s > Higher Is Better a . 159.22 |============================================================== b . 173.45 |=================================================================== c . 160.51 |============================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: FFTW - Precision: float - X Y Z: 512 GFLOP/s > Higher Is Better a . 136.09 |=================================================================== b . 133.27 |================================================================== c . 130.46 |================================================================ HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: FFTW - Precision: float - X Y Z: 128 GFLOP/s > Higher Is Better a . 175.04 |=================================================================== b . 176.18 |=================================================================== c . 175.27 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: FFTW - Precision: float - X Y Z: 256 GFLOP/s > Higher Is Better a . 345.60 |=================================================================== b . 331.45 |================================================================ c . 341.13 |================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: FFTW - Precision: float - X Y Z: 512 GFLOP/s > Higher Is Better a . 242.80 |=================================================================== b . 238.31 |================================================================== c . 236.92 |================================================================= HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: FFTW - Precision: double - X Y Z: 128 GFLOP/s > Higher Is Better a . 71.48 |==================================================== b . 66.64 |================================================= c . 92.64 |==================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: FFTW - Precision: double - X Y Z: 256 GFLOP/s > Higher Is Better a . 64.85 |==================================================================== b . 63.68 |=================================================================== c . 62.71 |================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: FFTW - Precision: double - X Y Z: 512 GFLOP/s > Higher Is Better a . 69.69 |==================================================================== b . 65.41 |================================================================ c . 65.12 |================================================================ HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: FFTW - Precision: float - X Y Z: 1024 GFLOP/s > Higher Is Better a . 151.72 |=================================================================== b . 152.47 |=================================================================== c . 152.04 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: Stock - Precision: float - X Y Z: 128 GFLOP/s > Higher Is Better a . 125.36 |=================================================================== b . 126.18 |=================================================================== c . 108.63 |========================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: Stock - Precision: float - X Y Z: 256 GFLOP/s > Higher Is Better a . 172.19 |=================================================================== b . 157.03 |============================================================= c . 159.46 |============================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: Stock - Precision: float - X Y Z: 512 GFLOP/s > Higher Is Better a . 119.58 |============================================================== b . 129.55 |=================================================================== c . 118.43 |============================================================= HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: FFTW - Precision: double - X Y Z: 128 GFLOP/s > Higher Is Better a . 89.76 |==================================================== b . 41.56 |======================== c . 115.40 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: FFTW - Precision: double - X Y Z: 256 GFLOP/s > Higher Is Better a . 130.15 |=============================================================== b . 138.93 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: FFTW - Precision: double - X Y Z: 512 GFLOP/s > Higher Is Better a . 123.79 |=================================================================== b . 122.95 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: FFTW - Precision: float - X Y Z: 1024 GFLOP/s > Higher Is Better a . 261.58 |=================================================================== b . 262.00 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: Stock - Precision: float - X Y Z: 128 GFLOP/s > Higher Is Better a . 161.82 |=================================================================== b . 161.36 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: Stock - Precision: float - X Y Z: 256 GFLOP/s > Higher Is Better a . 360.02 |=================================================================== b . 323.21 |============================================================ HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: Stock - Precision: float - X Y Z: 512 GFLOP/s > Higher Is Better a . 242.76 |================================================================== b . 245.52 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: FFTW - Precision: double - X Y Z: 1024 GFLOP/s > Higher Is Better a . 82.10 |==================================================================== b . 80.47 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: Stock - Precision: double - X Y Z: 128 GFLOP/s > Higher Is Better a . 89.02 |=================================================================== b . 90.01 |==================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: Stock - Precision: double - X Y Z: 256 GFLOP/s > Higher Is Better a . 65.75 |=================================================================== b . 67.00 |==================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: Stock - Precision: double - X Y Z: 512 GFLOP/s > Higher Is Better a . 72.03 |==================================================================== b . 71.31 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: Stock - Precision: float - X Y Z: 1024 GFLOP/s > Higher Is Better a . 152.49 |=================================================================== b . 152.92 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: FFTW - Precision: double - X Y Z: 1024 GFLOP/s > Higher Is Better a . 137.37 |=================================================================== b . 137.38 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: Stock - Precision: double - X Y Z: 128 GFLOP/s > Higher Is Better a . 115.20 |============================================================= b . 125.70 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: Stock - Precision: double - X Y Z: 256 GFLOP/s > Higher Is Better a . 149.78 |=================================================================== b . 146.84 |================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: Stock - Precision: double - X Y Z: 512 GFLOP/s > Higher Is Better a . 133.76 |=================================================================== b . 131.44 |================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: Stock - Precision: float - X Y Z: 1024 GFLOP/s > Higher Is Better a . 298.19 |=================================================================== b . 297.89 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: Stock - Precision: double - X Y Z: 1024 GFLOP/s > Higher Is Better a . 82.66 |==================================================================== b . 82.83 |==================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: Stock - Precision: double - X Y Z: 1024 GFLOP/s > Higher Is Better a . 154.89 |=================================================================== b . 154.81 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: FFTW - Precision: float-long - X Y Z: 128 GFLOP/s > Higher Is Better a . 143.40 |=================================================================== b . 132.64 |============================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: FFTW - Precision: float-long - X Y Z: 256 GFLOP/s > Higher Is Better a . 166.06 |=================================================================== b . 158.01 |================================================================ HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: FFTW - Precision: float-long - X Y Z: 512 GFLOP/s > Higher Is Better a . 134.08 |=================================================================== b . 133.67 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: FFTW - Precision: float-long - X Y Z: 128 GFLOP/s > Higher Is Better a . 165.32 |=============================================================== b . 175.74 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: FFTW - Precision: float-long - X Y Z: 256 GFLOP/s > Higher Is Better a . 323.08 |============================================================== b . 348.23 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: FFTW - Precision: float-long - X Y Z: 512 GFLOP/s > Higher Is Better a . 246.42 |=================================================================== b . 238.18 |================================================================= HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: FFTW - Precision: double-long - X Y Z: 128 GFLOP/s > Higher Is Better a . 29.78 |====================== b . 92.73 |==================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: FFTW - Precision: double-long - X Y Z: 256 GFLOP/s > Higher Is Better a . 67.45 |==================================================================== b . 63.59 |================================================================ HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: FFTW - Precision: double-long - X Y Z: 512 GFLOP/s > Higher Is Better a . 67.01 |==================================================================== b . 66.19 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: FFTW - Precision: float-long - X Y Z: 1024 GFLOP/s > Higher Is Better a . 152.25 |=================================================================== b . 153.36 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: Stock - Precision: float-long - X Y Z: 128 GFLOP/s > Higher Is Better a . 123.36 |=================================================================== b . 123.26 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: Stock - Precision: float-long - X Y Z: 256 GFLOP/s > Higher Is Better a . 162.02 |=================================================================== b . 158.12 |================================================================= HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: Stock - Precision: float-long - X Y Z: 512 GFLOP/s > Higher Is Better a . 128.23 |================================================================== b . 129.79 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: FFTW - Precision: double-long - X Y Z: 128 GFLOP/s > Higher Is Better a . 71.96 |==================================================================== b . 38.50 |==================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: FFTW - Precision: double-long - X Y Z: 256 GFLOP/s > Higher Is Better a . 127.35 |================================================================= b . 131.69 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: FFTW - Precision: double-long - X Y Z: 512 GFLOP/s > Higher Is Better a . 124.49 |=================================================================== b . 123.11 |================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: FFTW - Precision: float-long - X Y Z: 1024 GFLOP/s > Higher Is Better a . 262.19 |=================================================================== b . 262.09 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: Stock - Precision: float-long - X Y Z: 128 GFLOP/s > Higher Is Better a . 164.82 |=================================================================== b . 158.42 |================================================================ HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: Stock - Precision: float-long - X Y Z: 256 GFLOP/s > Higher Is Better a . 322.72 |================================================================== b . 327.72 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: Stock - Precision: float-long - X Y Z: 512 GFLOP/s > Higher Is Better a . 244.61 |=================================================================== b . 241.84 |================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: FFTW - Precision: double-long - X Y Z: 1024 GFLOP/s > Higher Is Better a . 82.82 |==================================================================== b . 81.97 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: Stock - Precision: double-long - X Y Z: 128 GFLOP/s > Higher Is Better a . 87.91 |================================================================== b . 90.23 |==================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: Stock - Precision: double-long - X Y Z: 256 GFLOP/s > Higher Is Better a . 67.43 |==================================================================== b . 65.55 |================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: Stock - Precision: double-long - X Y Z: 512 GFLOP/s > Higher Is Better a . 71.74 |==================================================================== b . 71.46 |==================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: Stock - Precision: float-long - X Y Z: 1024 GFLOP/s > Higher Is Better a . 153.32 |=================================================================== b . 153.99 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: FFTW - Precision: double-long - X Y Z: 1024 GFLOP/s > Higher Is Better a . 138.03 |=================================================================== b . 136.46 |================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: Stock - Precision: double-long - X Y Z: 128 GFLOP/s > Higher Is Better a . 120.20 |================================================================= b . 124.55 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: Stock - Precision: double-long - X Y Z: 256 GFLOP/s > Higher Is Better a . 156.74 |=================================================================== b . 157.55 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: Stock - Precision: double-long - X Y Z: 512 GFLOP/s > Higher Is Better a . 135.65 |=================================================================== b . 132.37 |================================================================= HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: Stock - Precision: float-long - X Y Z: 1024 GFLOP/s > Higher Is Better a . 299.64 |=================================================================== b . 297.94 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: Stock - Precision: double-long - X Y Z: 1024 GFLOP/s > Higher Is Better a . 82.72 |==================================================================== b . 82.77 |==================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: Stock - Precision: double-long - X Y Z: 1024 GFLOP/s > Higher Is Better a . 154.94 |=================================================================== b . 155.04 |=================================================================== OpenVINO 2023.2.dev Model: Face Detection FP16 - Device: CPU FPS > Higher Is Better e . 77.69 |======================== g . 104.31 |================================ h . 104.12 |================================ j . 193.11 |=========================================================== k . 191.20 |=========================================================== l . 218.22 |=================================================================== m . 218.39 |=================================================================== n . 217.79 |=================================================================== OpenVINO 2023.2.dev Model: Face Detection FP16 - Device: CPU ms < Lower Is Better e . 385.45 |=================================================================== g . 114.95 |==================== h . 115.13 |==================== j . 124.17 |====================== k . 125.39 |====================== l . 137.34 |======================== m . 137.23 |======================== n . 137.61 |======================== OpenVINO 2023.2.dev Model: Face Detection FP16-INT8 - Device: CPU FPS > Higher Is Better e . 165.82 |=========================== g . 196.21 |================================ h . 196.28 |================================ j . 370.50 |============================================================ k . 365.91 |=========================================================== l . 415.38 |=================================================================== m . 415.53 |=================================================================== n . 414.39 |=================================================================== OpenVINO 2023.2.dev Model: Face Detection FP16-INT8 - Device: CPU ms < Lower Is Better e . 360.89 |=================================================================== g . 244.29 |============================================= h . 244.11 |============================================= j . 258.62 |================================================ k . 261.89 |================================================= l . 288.36 |====================================================== m . 288.29 |====================================================== n . 289.07 |====================================================== OpenVINO 2023.2.dev Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU FPS > Higher Is Better e . 86847.05 |======================================= g . 90384.31 |======================================== h . 88444.43 |======================================= j . 115992.72 |=================================================== k . 103901.05 |============================================== l . 144299.06 |================================================================ m . 142293.67 |=============================================================== n . 142499.69 |=============================================================== OpenVINO 2023.2.dev Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU ms < Lower Is Better e . 0.61 |===================================================================== g . 0.51 |========================================================== h . 0.52 |=========================================================== j . 0.41 |============================================== k . 0.41 |============================================== l . 0.37 |========================================== m . 0.38 |=========================================== n . 0.38 |=========================================== OpenVINO 2023.2.dev Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU FPS > Higher Is Better e . 106187.70 |============================================= g . 131083.06 |======================================================= h . 131445.26 |======================================================= j . 114581.51 |================================================ k . 119756.16 |=================================================== l . 151691.73 |================================================================ m . 150804.01 |================================================================ n . 146682.31 |============================================================== OpenVINO 2023.2.dev Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU ms < Lower Is Better e . 0.48 |===================================================================== g . 0.30 |=========================================== h . 0.30 |=========================================== j . 0.31 |============================================= k . 0.31 |============================================= l . 0.29 |========================================== m . 0.29 |========================================== n . 0.29 |========================================== OpenVINO 2023.2.dev Model: Person Detection FP16 - Device: CPU FPS > Higher Is Better e . 290.36 |============================== g . 339.17 |==================================== h . 339.22 |==================================== j . 632.07 |================================================================== k . 626.67 |================================================================== l . 636.90 |=================================================================== m . 638.13 |=================================================================== n . 638.56 |=================================================================== OpenVINO 2023.2.dev Model: Person Detection FP16 - Device: CPU ms < Lower Is Better e . 103.21 |=================================================================== g . 35.35 |======================= h . 35.35 |======================= j . 37.93 |========================= k . 38.26 |========================= l . 47.07 |=============================== m . 46.98 |============================== n . 46.94 |============================== OpenVINO 2023.2.dev Model: Person Detection FP32 - Device: CPU FPS > Higher Is Better e . 290.88 |============================== g . 338.84 |=================================== h . 338.61 |=================================== j . 631.31 |================================================================== k . 627.12 |================================================================== l . 636.48 |=================================================================== m . 639.58 |=================================================================== n . 635.92 |=================================================================== OpenVINO 2023.2.dev Model: Person Detection FP32 - Device: CPU ms < Lower Is Better e . 103.01 |=================================================================== g . 35.39 |======================= h . 35.41 |======================= j . 37.98 |========================= k . 38.23 |========================= l . 47.10 |=============================== m . 46.87 |============================== n . 47.14 |=============================== OpenVINO 2023.2.dev Model: Weld Porosity Detection FP16-INT8 - Device: CPU FPS > Higher Is Better e . 16489.33 |======================= g . 19358.98 |=========================== h . 19208.93 |========================== j . 35303.47 |================================================ k . 34620.99 |=============================================== l . 47357.41 |================================================================= m . 47468.22 |================================================================= n . 47369.39 |================================================================= OpenVINO 2023.2.dev Model: Weld Porosity Detection FP16-INT8 - Device: CPU ms < Lower Is Better e . 3.51 |===================================================================== g . 2.47 |================================================= h . 2.49 |================================================= j . 2.68 |===================================================== k . 2.74 |====================================================== l . 2.52 |================================================== m . 2.51 |================================================= n . 2.52 |================================================== OpenVINO 2023.2.dev Model: Weld Porosity Detection FP16 - Device: CPU FPS > Higher Is Better e . 9078.33 |====================== g . 10978.58 |========================== h . 11783.36 |============================ j . 21815.71 |==================================================== k . 21635.47 |==================================================== l . 27232.91 |================================================================= m . 27109.50 |================================================================= n . 27112.85 |================================================================= OpenVINO 2023.2.dev Model: Weld Porosity Detection FP16 - Device: CPU ms < Lower Is Better e . 6.44 |===================================================================== g . 4.36 |=============================================== h . 4.06 |============================================ j . 4.38 |=============================================== k . 4.42 |=============================================== l . 4.35 |=============================================== m . 4.35 |=============================================== n . 4.35 |=============================================== OpenVINO 2023.2.dev Model: Vehicle Detection FP16-INT8 - Device: CPU FPS > Higher Is Better e . 3221.62 |================================== g . 3319.81 |=================================== h . 3314.00 |=================================== j . 6234.26 |================================================================== k . 6196.74 |================================================================== l . 5831.93 |============================================================== m . 5825.24 |============================================================== n . 5799.67 |============================================================= OpenVINO 2023.2.dev Model: Vehicle Detection FP16-INT8 - Device: CPU ms < Lower Is Better e . 18.43 |============================================================= g . 14.44 |================================================ h . 14.46 |================================================ j . 15.33 |=================================================== k . 15.43 |=================================================== l . 20.51 |==================================================================== m . 20.53 |==================================================================== n . 20.62 |==================================================================== OpenVINO 2023.2.dev Model: Vehicle Detection FP16 - Device: CPU FPS > Higher Is Better e . 1878.87 |================================ g . 1884.46 |================================ h . 1889.02 |================================ j . 3484.18 |=========================================================== k . 3465.57 |=========================================================== l . 3893.77 |================================================================== m . 3895.49 |================================================================== n . 3895.01 |================================================================== OpenVINO 2023.2.dev Model: Vehicle Detection FP16 - Device: CPU ms < Lower Is Better e . 15.86 |==================================================================== g . 6.35 |=========================== h . 6.34 |=========================== j . 6.87 |============================= k . 6.90 |============================== l . 7.69 |================================= m . 7.69 |================================= n . 7.69 |================================= OpenVINO 2023.2.dev Model: Person Vehicle Bike Detection FP16 - Device: CPU FPS > Higher Is Better e . 3566.26 |=============================== g . 3685.78 |================================ h . 3678.97 |================================ j . 6992.06 |============================================================ k . 7049.72 |============================================================= l . 7617.42 |================================================================== m . 7626.39 |================================================================== n . 7650.29 |================================================================== OpenVINO 2023.2.dev Model: Person Vehicle Bike Detection FP16 - Device: CPU ms < Lower Is Better e . 16.72 |==================================================================== g . 13.00 |===================================================== h . 13.03 |===================================================== j . 13.68 |======================================================== k . 13.59 |======================================================= l . 15.66 |================================================================ m . 15.63 |================================================================ n . 15.59 |=============================================================== OpenVINO 2023.2.dev Model: Machine Translation EN To DE FP16 - Device: CPU FPS > Higher Is Better e . 462.66 |====================================== g . 433.90 |==================================== h . 430.23 |==================================== j . 806.26 |=================================================================== k . 803.87 |=================================================================== l . 733.98 |============================================================= m . 744.86 |============================================================== n . 729.58 |============================================================= OpenVINO 2023.2.dev Model: Machine Translation EN To DE FP16 - Device: CPU ms < Lower Is Better e . 64.66 |==================================================================== g . 27.53 |============================= h . 27.75 |============================= j . 29.63 |=============================== k . 29.75 |=============================== l . 40.61 |=========================================== m . 40.04 |========================================== n . 40.90 |=========================================== OpenVINO 2023.2.dev Model: Face Detection Retail FP16 - Device: CPU FPS > Higher Is Better e . 6106.91 |=========================== g . 6581.71 |============================= h . 6566.24 |============================= j . 12561.59 |======================================================= k . 12534.63 |======================================================= l . 14938.83 |================================================================= m . 14932.70 |================================================================= n . 14888.49 |================================================================= OpenVINO 2023.2.dev Model: Face Detection Retail FP16 - Device: CPU ms < Lower Is Better e . 9.66 |===================================================================== g . 7.28 |==================================================== h . 7.30 |==================================================== j . 7.62 |====================================================== k . 7.64 |======================================================= l . 8.02 |========================================================= m . 8.02 |========================================================= n . 8.05 |========================================================== OpenVINO 2023.2.dev Model: Face Detection Retail FP16-INT8 - Device: CPU FPS > Higher Is Better e . 9344.43 |============================= g . 8871.46 |=========================== h . 8855.95 |=========================== j . 16935.65 |==================================================== k . 16935.03 |==================================================== l . 21075.26 |================================================================= m . 21071.09 |================================================================= n . 21033.04 |================================================================= OpenVINO 2023.2.dev Model: Face Detection Retail FP16-INT8 - Device: CPU ms < Lower Is Better e . 6.28 |===================================================================== g . 5.40 |=========================================================== h . 5.41 |=========================================================== j . 5.65 |============================================================== k . 5.65 |============================================================== l . 5.68 |============================================================== m . 5.68 |============================================================== n . 5.69 |=============================================================== OpenVINO 2023.2.dev Model: Handwritten English Recognition FP16 - Device: CPU FPS > Higher Is Better e . 1545.36 |======================= g . 1979.56 |============================= h . 1988.30 |============================== j . 3910.94 |========================================================== k . 3918.19 |========================================================== l . 4387.28 |================================================================= m . 4379.43 |================================================================= n . 4433.69 |================================================================== OpenVINO 2023.2.dev Model: Handwritten English Recognition FP16 - Device: CPU ms < Lower Is Better e . 38.54 |==================================================================== g . 24.23 |=========================================== h . 24.12 |=========================================== j . 24.52 |=========================================== k . 24.48 |=========================================== l . 27.30 |================================================ m . 27.35 |================================================ n . 27.04 |================================================ OpenVINO 2023.2.dev Model: Handwritten English Recognition FP16-INT8 - Device: CPU FPS > Higher Is Better e . 1224.11 |=========================== g . 1200.82 |========================== h . 1192.76 |========================== j . 2375.20 |==================================================== k . 2377.19 |==================================================== l . 3004.85 |================================================================== m . 3004.85 |================================================================== n . 2991.51 |================================================================== OpenVINO 2023.2.dev Model: Handwritten English Recognition FP16-INT8 - Device: CPU ms < Lower Is Better e . 48.77 |==================================================================== g . 39.95 |======================================================== h . 40.22 |======================================================== j . 40.39 |======================================================== k . 40.36 |======================================================== l . 39.91 |======================================================== m . 39.91 |======================================================== n . 40.09 |======================================================== OpenVINO 2023.2.dev Model: Road Segmentation ADAS FP16 - Device: CPU FPS > Higher Is Better e . 751.14 |================================ g . 682.77 |============================= h . 681.90 |============================= j . 1283.22 |======================================================= k . 1273.73 |======================================================= l . 1530.63 |================================================================== m . 1531.37 |================================================================== n . 1530.84 |================================================================== OpenVINO 2023.2.dev Model: Road Segmentation ADAS FP16 - Device: CPU ms < Lower Is Better e . 39.86 |==================================================================== g . 17.55 |============================== h . 17.58 |============================== j . 18.68 |================================ k . 18.82 |================================ l . 19.58 |================================= m . 19.57 |================================= n . 19.58 |================================= OpenVINO 2023.2.dev Model: Road Segmentation ADAS FP16-INT8 - Device: CPU FPS > Higher Is Better e . 1101.87 |====================================== g . 923.91 |================================ h . 925.43 |================================ j . 1712.71 |=========================================================== k . 1709.38 |=========================================================== l . 1914.91 |================================================================== m . 1915.98 |================================================================== n . 1912.82 |================================================================== OpenVINO 2023.2.dev Model: Road Segmentation ADAS FP16-INT8 - Device: CPU ms < Lower Is Better e . 54.30 |=========================================================== g . 51.91 |======================================================== h . 51.84 |======================================================== j . 56.00 |============================================================= k . 56.11 |============================================================= l . 62.61 |==================================================================== m . 62.56 |==================================================================== n . 62.67 |==================================================================== OSPRay Studio 0.13 Camera: 1 - Resolution: 4K - Samples Per Pixel: 1 - Renderer: Path Tracer - Acceleration: CPU ms < Lower Is Better a . 889 |=============================== b . 889 |=============================== d . 894 |=============================== e . 1644 |========================================================= f . 1647 |========================================================= g . 1984 |===================================================================== h . 1975 |===================================================================== j . 1366 |================================================ k . 1361 |=============================================== n . 889 |=============================== OSPRay Studio 0.13 Camera: 2 - Resolution: 4K - Samples Per Pixel: 1 - Renderer: Path Tracer - Acceleration: CPU ms < Lower Is Better a . 907 |=============================== b . 908 |=============================== d . 910 |================================ e . 1663 |========================================================== f . 1661 |========================================================== g . 1990 |===================================================================== h . 1989 |===================================================================== j . 1535 |===================================================== k . 1381 |================================================ n . 903 |=============================== OSPRay Studio 0.13 Camera: 3 - Resolution: 4K - Samples Per Pixel: 1 - Renderer: Path Tracer - Acceleration: CPU ms < Lower Is Better a . 1066 |=============================== b . 1064 |=============================== d . 1064 |=============================== e . 1962 |========================================================== f . 1962 |========================================================== g . 2352 |===================================================================== h . 2345 |===================================================================== j . 1691 |================================================== k . 1672 |================================================= n . 1057 |=============================== OSPRay Studio 0.13 Camera: 1 - Resolution: 4K - Samples Per Pixel: 16 - Renderer: Path Tracer - Acceleration: CPU ms < Lower Is Better a . 14067 |========================== b . 13991 |========================== d . 14042 |========================== e . 30876 |========================================================= f . 30951 |========================================================= g . 36833 |==================================================================== h . 36575 |==================================================================== j . 31587 |========================================================== k . 21000 |======================================= n . 14017 |========================== OSPRay Studio 0.13 Camera: 1 - Resolution: 4K - Samples Per Pixel: 32 - Renderer: Path Tracer - Acceleration: CPU ms < Lower Is Better a . 33358 |================================= b . 33490 |================================= d . 33652 |================================= e . 57130 |========================================================= f . 57572 |========================================================= g . 68562 |==================================================================== h . 68355 |==================================================================== j . 51593 |=================================================== k . 48393 |================================================ n . 33085 |================================= OSPRay Studio 0.13 Camera: 2 - Resolution: 4K - Samples Per Pixel: 16 - Renderer: Path Tracer - Acceleration: CPU ms < Lower Is Better a . 14223 |========================== b . 14248 |========================== d . 14338 |=========================== e . 31373 |========================================================== f . 31194 |========================================================== g . 36770 |==================================================================== h . 36787 |==================================================================== j . 22407 |========================================= k . 22062 |========================================= n . 14289 |========================== OSPRay Studio 0.13 Camera: 2 - Resolution: 4K - Samples Per Pixel: 32 - Renderer: Path Tracer - Acceleration: CPU ms < Lower Is Better a . 34608 |================================== b . 33567 |================================= d . 33817 |================================== e . 58032 |========================================================== f . 58436 |========================================================== g . 68506 |==================================================================== h . 68593 |==================================================================== j . 51940 |=================================================== k . 52535 |==================================================== n . 33789 |================================= OSPRay Studio 0.13 Camera: 3 - Resolution: 4K - Samples Per Pixel: 16 - Renderer: Path Tracer - Acceleration: CPU ms < Lower Is Better a . 16770 |=========================== b . 16786 |=========================== d . 16765 |=========================== e . 36028 |========================================================== f . 36109 |========================================================== g . 42592 |==================================================================== h . 42412 |==================================================================== j . 30736 |================================================= k . 34459 |======================================================= n . 16672 |=========================== OSPRay Studio 0.13 Camera: 3 - Resolution: 4K - Samples Per Pixel: 32 - Renderer: Path Tracer - Acceleration: CPU ms < Lower Is Better a . 38573 |================================= b . 38554 |================================= d . 39029 |================================= e . 67291 |========================================================= f . 67337 |========================================================= g . 80104 |==================================================================== h . 79992 |==================================================================== j . 60905 |==================================================== k . 59689 |=================================================== n . 38979 |================================= OSPRay Studio 0.13 Camera: 1 - Resolution: 1080p - Samples Per Pixel: 1 - Renderer: Path Tracer - Acceleration: CPU ms < Lower Is Better a . 225 |================================ b . 226 |================================ d . 227 |================================ e . 416 |========================================================== f . 416 |========================================================== g . 500 |====================================================================== h . 500 |====================================================================== j . 356 |================================================== k . 344 |================================================ n . 225 |================================ OSPRay Studio 0.13 Camera: 2 - Resolution: 1080p - Samples Per Pixel: 1 - Renderer: Path Tracer - Acceleration: CPU ms < Lower Is Better a . 230 |================================ b . 230 |================================ d . 231 |================================ e . 421 |========================================================== f . 422 |========================================================== g . 505 |====================================================================== h . 505 |====================================================================== j . 361 |================================================== k . 370 |=================================================== n . 230 |================================ OSPRay Studio 0.13 Camera: 3 - Resolution: 1080p - Samples Per Pixel: 1 - Renderer: Path Tracer - Acceleration: CPU ms < Lower Is Better a . 269 |================================ b . 268 |================================ d . 270 |================================ e . 496 |========================================================== f . 497 |========================================================== g . 595 |====================================================================== h . 595 |====================================================================== j . 420 |================================================= k . 450 |===================================================== n . 268 |================================ OSPRay Studio 0.13 Camera: 1 - Resolution: 1080p - Samples Per Pixel: 16 - Renderer: Path Tracer - Acceleration: CPU ms < Lower Is Better a . 3539 |=============================== b . 3542 |=============================== d . 3558 |=============================== e . 6633 |========================================================== f . 6628 |========================================================== g . 7939 |===================================================================== h . 7952 |===================================================================== j . 5349 |============================================== k . 5771 |================================================== n . 3545 |=============================== OSPRay Studio 0.13 Camera: 1 - Resolution: 1080p - Samples Per Pixel: 32 - Renderer: Path Tracer - Acceleration: CPU ms < Lower Is Better a . 7076 |============================== b . 7113 |============================== d . 7142 |============================== e . 13272 |========================================================= f . 13231 |======================================================== g . 15955 |==================================================================== h . 15942 |==================================================================== j . 10852 |============================================== k . 10581 |============================================= n . 7076 |============================== OSPRay Studio 0.13 Camera: 2 - Resolution: 1080p - Samples Per Pixel: 16 - Renderer: Path Tracer - Acceleration: CPU ms < Lower Is Better a . 3620 |=============================== b . 3594 |=============================== d . 3636 |=============================== e . 6711 |========================================================== f . 6711 |========================================================== g . 8009 |===================================================================== h . 8010 |===================================================================== j . 5659 |================================================= k . 5812 |================================================== n . 3605 |=============================== OSPRay Studio 0.13 Camera: 2 - Resolution: 1080p - Samples Per Pixel: 32 - Renderer: Path Tracer - Acceleration: CPU ms < Lower Is Better a . 7192 |============================== b . 7193 |============================== d . 7245 |=============================== e . 13393 |======================================================== g . 16151 |==================================================================== h . 16114 |==================================================================== j . 11801 |================================================== k . 11652 |================================================= n . 7194 |============================== OSPRay Studio 0.13 Camera: 3 - Resolution: 1080p - Samples Per Pixel: 16 - Renderer: Path Tracer - Acceleration: CPU ms < Lower Is Better a . 4239 |=============================== b . 4213 |=============================== d . 4258 |=============================== e . 7892 |========================================================= g . 9424 |===================================================================== h . 9487 |===================================================================== j . 6496 |=============================================== k . 7011 |=================================================== n . 4206 |=============================== OSPRay Studio 0.13 Camera: 3 - Resolution: 1080p - Samples Per Pixel: 32 - Renderer: Path Tracer - Acceleration: CPU ms < Lower Is Better a . 8459 |============================== b . 8429 |============================== d . 8493 |============================== e . 15787 |========================================================= g . 18877 |==================================================================== h . 18945 |==================================================================== j . 13319 |================================================ k . 13049 |=============================================== n . 8428 |============================== QMCPACK 3.17.1 Input: H4_ae Total Execution Time - Seconds < Lower Is Better l . 12.52 |=================================================================== m . 12.68 |==================================================================== n . 12.70 |==================================================================== QMCPACK 3.17.1 Input: Li2_STO_ae Total Execution Time - Seconds < Lower Is Better l . 99.82 |==================================================================== m . 98.18 |=================================================================== n . 99.26 |==================================================================== QMCPACK 3.17.1 Input: LiH_ae_MSD Total Execution Time - Seconds < Lower Is Better l . 94.27 |==================================================================== m . 94.02 |==================================================================== n . 94.30 |==================================================================== QMCPACK 3.17.1 Input: simple-H2O Total Execution Time - Seconds < Lower Is Better l . 29.29 |==================================================================== m . 29.19 |==================================================================== n . 29.15 |==================================================================== QMCPACK 3.17.1 Input: O_ae_pyscf_UHF Total Execution Time - Seconds < Lower Is Better l . 214.65 |=================================================================== m . 207.84 |================================================================= n . 208.62 |================================================================= QMCPACK 3.17.1 Input: FeCO6_b3lyp_gms Total Execution Time - Seconds < Lower Is Better l . 128.73 |=================================================================== m . 129.20 |=================================================================== n . 129.23 |=================================================================== Timed Gem5 Compilation 23.0.1 Time To Compile Seconds < Lower Is Better e . 197.55 |============================================================= g . 206.08 |================================================================ h . 216.88 |=================================================================== j . 195.49 |============================================================ k . 197.95 |============================================================= l . 168.58 |==================================================== m . 162.39 |================================================== n . 165.81 |===================================================