dddas

AMD Ryzen Threadripper 3970X 32-Core testing with a ASUS ROG ZENITH II EXTREME (1603 BIOS) and AMD Radeon RX 5700 8GB on Ubuntu 22.04 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 2306247-NE-DDDAS346146
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
Show Result Confidence Charts

Limit displaying results to tests within:

AV1 2 Tests
BLAS (Basic Linear Algebra Sub-Routine) Tests 3 Tests
C/C++ Compiler Tests 3 Tests
CPU Massive 5 Tests
Creator Workloads 9 Tests
Database Test Suite 2 Tests
Encoding 4 Tests
Fortran Tests 5 Tests
HPC - High Performance Computing 10 Tests
Common Kernel Benchmarks 2 Tests
Machine Learning 3 Tests
MPI Benchmarks 4 Tests
Multi-Core 8 Tests
Intel oneAPI 4 Tests
OpenMPI Tests 11 Tests
Python Tests 6 Tests
Scientific Computing 5 Tests
Server 2 Tests
Server CPU Tests 5 Tests
Video Encoding 3 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

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
June 23 2023
  13 Hours, 58 Minutes
b
June 24 2023
  4 Hours, 14 Minutes
Invert Hiding All Results Option
  9 Hours, 6 Minutes
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):

dddas AMD Ryzen Threadripper 3970X 32-Core testing with a ASUS ROG ZENITH II EXTREME (1603 BIOS) and AMD Radeon RX 5700 8GB on Ubuntu 22.04 via the Phoronix Test Suite. a: Processor: AMD Ryzen Threadripper 3970X 32-Core @ 3.70GHz (32 Cores / 64 Threads), Motherboard: ASUS ROG ZENITH II EXTREME (1603 BIOS), Chipset: AMD Starship/Matisse, Memory: 64GB, Disk: Samsung SSD 980 PRO 500GB, Graphics: AMD Radeon RX 5700 8GB (1750/875MHz), Audio: AMD Navi 10 HDMI Audio, Monitor: ASUS VP28U, Network: Aquantia AQC107 NBase-T/IEEE + Intel I211 + Intel Wi-Fi 6 AX200 OS: Ubuntu 22.04, Kernel: 5.19.0-051900rc7-generic (x86_64), Desktop: GNOME Shell 42.2, Display Server: X Server + Wayland, OpenGL: 4.6 Mesa 22.0.1 (LLVM 13.0.1 DRM 3.47), Vulkan: 1.2.204, Compiler: GCC 11.3.0, File-System: ext4, Screen Resolution: 3840x2160 b: Processor: AMD Ryzen Threadripper 3970X 32-Core @ 3.70GHz (32 Cores / 64 Threads), Motherboard: ASUS ROG ZENITH II EXTREME (1603 BIOS), Chipset: AMD Starship/Matisse, Memory: 64GB, Disk: Samsung SSD 980 PRO 500GB, Graphics: AMD Radeon RX 5700 8GB (1750/875MHz), Audio: AMD Navi 10 HDMI Audio, Monitor: ASUS VP28U, Network: Aquantia AQC107 NBase-T/IEEE + Intel I211 + Intel Wi-Fi 6 AX200 OS: Ubuntu 22.04, Kernel: 5.19.0-051900rc7-generic (x86_64), Desktop: GNOME Shell 42.2, Display Server: X Server + Wayland, OpenGL: 4.6 Mesa 22.0.1 (LLVM 13.0.1 DRM 3.47), Vulkan: 1.2.204, Compiler: GCC 11.3.0, File-System: ext4, Screen Resolution: 3840x2160 Stress-NG 0.15.10 Test: Hash Bogo Ops/s > Higher Is Better a . 7627578.66 |=============================================================== b . 7624159.24 |=============================================================== Stress-NG 0.15.10 Test: MMAP Bogo Ops/s > Higher Is Better a . 437.11 |=================================================================== b . 439.24 |=================================================================== Stress-NG 0.15.10 Test: NUMA Bogo Ops/s > Higher Is Better a . 752.30 |=================================================================== b . 741.66 |================================================================== Stress-NG 0.15.10 Test: Pipe Bogo Ops/s > Higher Is Better a . 18809740.35 |===================================================== b . 22201912.16 |============================================================== libxsmm 2-1.17-3645 M N K: 32 GFLOPS/s > Higher Is Better a . 160.5 |==================================================================== b . 160.7 |==================================================================== Stress-NG 0.15.10 Test: Poll Bogo Ops/s > Higher Is Better a . 4084623.29 |=============================================================== b . 4101817.96 |=============================================================== Stress-NG 0.15.10 Test: Zlib Bogo Ops/s > Higher Is Better a . 4517.78 |================================================================== b . 4518.88 |================================================================== Stress-NG 0.15.10 Test: Futex Bogo Ops/s > Higher Is Better a . 4610857.40 |=============================================================== b . 4644715.00 |=============================================================== Stress-NG 0.15.10 Test: MEMFD Bogo Ops/s > Higher Is Better a . 395.11 |=================================================================== b . 394.50 |=================================================================== Stress-NG 0.15.10 Test: Mutex Bogo Ops/s > Higher Is Better a . 18827346.28 |============================================================== b . 18816044.49 |============================================================== Stress-NG 0.15.10 Test: Atomic Bogo Ops/s > Higher Is Better a . 480.06 |=================================================================== b . 480.51 |=================================================================== Stress-NG 0.15.10 Test: Crypto Bogo Ops/s > Higher Is Better a . 78260.17 |================================================================= b . 78455.19 |================================================================= Stress-NG 0.15.10 Test: Malloc Bogo Ops/s > Higher Is Better a . 92853207.13 |============================================================== b . 92812375.37 |============================================================== Stress-NG 0.15.10 Test: Cloning Bogo Ops/s > Higher Is Better a . 3354.40 |================================================================== b . 3360.52 |================================================================== Stress-NG 0.15.10 Test: Forking Bogo Ops/s > Higher Is Better a . 51344.69 |================================================================= b . 51160.22 |================================================================= Stress-NG 0.15.10 Test: Pthread Bogo Ops/s > Higher Is Better a . 128353.64 |================================================================ b . 128387.57 |================================================================ Stress-NG 0.15.10 Test: AVL Tree Bogo Ops/s > Higher Is Better a . 283.41 |=================================================================== b . 282.42 |=================================================================== Stress-NG 0.15.10 Test: IO_uring Bogo Ops/s > Higher Is Better a . 439798.24 |================================================================ b . 440335.12 |================================================================ Stress-NG 0.15.10 Test: SENDFILE Bogo Ops/s > Higher Is Better a . 515575.47 |============================================================== b . 528847.31 |================================================================ Stress-NG 0.15.10 Test: CPU Cache Bogo Ops/s > Higher Is Better a . 1624118.54 |=============================================================== b . 1535034.64 |============================================================ Stress-NG 0.15.10 Test: CPU Stress Bogo Ops/s > Higher Is Better a . 82729.76 |================================================================= b . 82887.24 |================================================================= Stress-NG 0.15.10 Test: Semaphores Bogo Ops/s > Higher Is Better a . 66510329.66 |========================================================== b . 71041068.48 |============================================================== Stress-NG 0.15.10 Test: Matrix Math Bogo Ops/s > Higher Is Better a . 199178.68 |================================================================ b . 200423.60 |================================================================ Laghos 3.1 Test: Sedov Blast Wave, ube_922_hex.mesh Major Kernels Total Rate > Higher Is Better a . 264.34 |=================================================================== b . 265.39 |=================================================================== Stress-NG 0.15.10 Test: Vector Math Bogo Ops/s > Higher Is Better a . 224417.23 |================================================================ b . 224460.71 |================================================================ Stress-NG 0.15.10 Test: Function Call Bogo Ops/s > Higher Is Better a . 24278.34 |================================================================= b . 24275.23 |================================================================= Stress-NG 0.15.10 Test: x86_64 RdRand Stress-NG 0.15.10 Test: Floating Point Bogo Ops/s > Higher Is Better a . 11201.44 |================================================================= b . 11221.55 |================================================================= Stress-NG 0.15.10 Test: Matrix 3D Math Bogo Ops/s > Higher Is Better a . 2806.09 |================================================================== b . 2795.85 |================================================================== Stress-NG 0.15.10 Test: Memory Copying Bogo Ops/s > Higher Is Better a . 10973.65 |================================================================= b . 10984.91 |================================================================= Stress-NG 0.15.10 Test: Vector Shuffle Bogo Ops/s > Higher Is Better a . 22825.44 |================================================================= b . 22200.86 |=============================================================== Stress-NG 0.15.10 Test: Socket Activity Bogo Ops/s > Higher Is Better a . 3072.80 |===================== b . 9580.27 |================================================================== Stress-NG 0.15.10 Test: Wide Vector Math Bogo Ops/s > Higher Is Better a . 1501239.29 |=============================================================== b . 1496970.66 |=============================================================== Stress-NG 0.15.10 Test: Context Switching Bogo Ops/s > Higher Is Better a . 11409509.77 |============================================================= b . 11620881.04 |============================================================== Stress-NG 0.15.10 Test: Fused Multiply-Add Bogo Ops/s > Higher Is Better a . 33507543.08 |============================================================== b . 33539318.97 |============================================================== Stress-NG 0.15.10 Test: Vector Floating Point Bogo Ops/s > Higher Is Better a . 94803.76 |================================================================ b . 95693.93 |================================================================= Stress-NG 0.15.10 Test: Glibc C String Functions Bogo Ops/s > Higher Is Better a . 33453867.32 |============================================================== b . 33092079.25 |============================================================= Stress-NG 0.15.10 Test: Glibc Qsort Data Sorting Bogo Ops/s > Higher Is Better a . 942.22 |=================================================================== b . 943.84 |=================================================================== libxsmm 2-1.17-3645 M N K: 64 GFLOPS/s > Higher Is Better a . 318.5 |==================================================================== b . 318.7 |==================================================================== Stress-NG 0.15.10 Test: System V Message Passing Bogo Ops/s > Higher Is Better a . 10692419.88 |============================================================== b . 10677047.79 |============================================================== libxsmm 2-1.17-3645 M N K: 256 GFLOPS/s > Higher Is Better a . 910.4 |==================================================================== b . 907.4 |==================================================================== libxsmm 2-1.17-3645 M N K: 128 GFLOPS/s > Higher Is Better a . 635.8 |==================================================================== b . 635.4 |==================================================================== Laghos 3.1 Test: Triple Point Problem Major Kernels Total Rate > Higher Is Better a . 220.46 |=================================================================== b . 219.12 |=================================================================== Palabos 2.3 Grid Size: 1000 Mega Site Updates Per Second > Higher Is Better Opus Codec Encoding 1.4 WAV To Opus Encode Seconds < Lower Is Better a . 28.70 |==================================================================== b . 28.83 |==================================================================== Palabos 2.3 Grid Size: 500 Mega Site Updates Per Second > Higher Is Better a . 143.85 |=================================================================== b . 144.06 |=================================================================== Palabos 2.3 Grid Size: 100 Mega Site Updates Per Second > Higher Is Better a . 121.93 |=================================================================== b . 122.23 |=================================================================== Palabos 2.3 Grid Size: 400 Mega Site Updates Per Second > Higher Is Better a . 139.30 |=================================================================== b . 140.08 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.3 Test: r2c - Backend: Stock - Precision: double-long - X Y Z: 256 GFLOP/s > Higher Is Better a . 30.14 |==================================================================== b . 30.29 |==================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.3 Test: r2c - Backend: Stock - Precision: double-long - X Y Z: 512 GFLOP/s > Higher Is Better a . 30.01 |==================================================================== b . 30.04 |==================================================================== Xonotic 0.8.6 Resolution: 1920 x 1080 - Effects Quality: Low Frames Per Second > Higher Is Better a . 671.42 |=================================================================== b . 669.86 |=================================================================== Xonotic 0.8.6 Resolution: 1920 x 1200 - Effects Quality: Low Frames Per Second > Higher Is Better a . 671.95 |=================================================================== b . 676.08 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.3 Test: c2c - Backend: Stock - Precision: double-long - X Y Z: 128 GFLOP/s > Higher Is Better a . 26.55 |=================================================================== b . 26.81 |==================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.3 Test: c2c - Backend: Stock - Precision: double-long - X Y Z: 256 GFLOP/s > Higher Is Better a . 13.88 |==================================================================== b . 13.85 |==================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.3 Test: r2c - Backend: FFTW - Precision: double-long - X Y Z: 256 GFLOP/s > Higher Is Better a . 27.43 |==================================================================== b . 27.27 |==================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.3 Test: r2c - Backend: FFTW - Precision: double-long - X Y Z: 512 GFLOP/s > Higher Is Better a . 27.71 |==================================================================== b . 27.73 |==================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.3 Test: r2c - Backend: FFTW - Precision: double-long - X Y Z: 128 GFLOP/s > Higher Is Better a . 56.45 |==================================================================== b . 55.85 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.3 Test: c2c - Backend: FFTW - Precision: double-long - X Y Z: 512 GFLOP/s > Higher Is Better a . 15.35 |==================================================================== b . 15.35 |==================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.3 Test: c2c - Backend: FFTW - Precision: double-long - X Y Z: 256 GFLOP/s > Higher Is Better a . 13.76 |==================================================================== b . 13.79 |==================================================================== eSpeak-NG Speech Engine 1.51 Text-To-Speech Synthesis Seconds < Lower Is Better a . 31.08 |=================================================================== b . 31.49 |==================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.3 Test: c2c - Backend: Stock - Precision: double-long - X Y Z: 512 GFLOP/s > Higher Is Better a . 15.41 |==================================================================== b . 15.41 |==================================================================== Xonotic 0.8.6 Resolution: 2560 x 1440 - Effects Quality: Low Frames Per Second > Higher Is Better a . 673.17 |================================================================== b . 687.49 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.3 Test: r2c - Backend: Stock - Precision: double-long - X Y Z: 128 GFLOP/s > Higher Is Better a . 51.88 |==================================================================== b . 50.93 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.3 Test: c2c - Backend: FFTW - Precision: double-long - X Y Z: 128 GFLOP/s > Higher Is Better a . 30.80 |==================================================================== b . 30.86 |==================================================================== Palabos 2.3 Grid Size: 4000 Mega Site Updates Per Second > Higher Is Better Xonotic 0.8.6 Resolution: 3840 x 2160 - Effects Quality: Low Frames Per Second > Higher Is Better a . 670.04 |================================================================== b . 675.84 |=================================================================== Xonotic 0.8.6 Resolution: 1920 x 1080 - Effects Quality: High Frames Per Second > Higher Is Better a . 561.44 |=================================================================== b . 563.79 |=================================================================== Xonotic 0.8.6 Resolution: 1920 x 1200 - Effects Quality: High Frames Per Second > Higher Is Better a . 561.01 |================================================================== b . 567.94 |=================================================================== Xonotic 0.8.6 Resolution: 2560 x 1440 - Effects Quality: High Frames Per Second > Higher Is Better a . 560.97 |================================================================== b . 567.98 |=================================================================== Xonotic 0.8.6 Resolution: 3840 x 2160 - Effects Quality: High Frames Per Second > Higher Is Better a . 467.69 |=================================================================== b . 469.75 |=================================================================== Z3 Theorem Prover 4.12.1 SMT File: 2.smt2 Seconds < Lower Is Better a . 76.01 |==================================================================== b . 76.12 |==================================================================== Xonotic 0.8.6 Resolution: 1920 x 1080 - Effects Quality: Ultra Frames Per Second > Higher Is Better a . 518.67 |================================================================== b . 524.55 |=================================================================== Z3 Theorem Prover 4.12.1 SMT File: 1.smt2 Seconds < Lower Is Better a . 29.93 |==================================================================== b . 29.90 |==================================================================== Remhos 1.0 Test: Sample Remap Example Seconds < Lower Is Better a . 23.54 |==================================================================== b . 23.65 |==================================================================== Xonotic 0.8.6 Resolution: 1920 x 1200 - Effects Quality: Ultra Frames Per Second > Higher Is Better a . 521.50 |=================================================================== b . 521.20 |=================================================================== Xonotic 0.8.6 Resolution: 2560 x 1440 - Effects Quality: Ultra Frames Per Second > Higher Is Better a . 520.79 |================================================================== b . 527.21 |=================================================================== Xonotic 0.8.6 Resolution: 3840 x 2160 - Effects Quality: Ultra Frames Per Second > Higher Is Better a . 420.75 |=================================================================== b . 423.33 |=================================================================== Xonotic 0.8.6 Resolution: 1920 x 1080 - Effects Quality: Ultimate Frames Per Second > Higher Is Better a . 386.94 |=================================================================== b . 386.28 |=================================================================== Xonotic 0.8.6 Resolution: 1920 x 1200 - Effects Quality: Ultimate Frames Per Second > Higher Is Better a . 384.77 |=================================================================== b . 386.81 |=================================================================== Xonotic 0.8.6 Resolution: 2560 x 1440 - Effects Quality: Ultimate Frames Per Second > Higher Is Better a . 384.02 |=================================================================== b . 381.32 |=================================================================== Xonotic 0.8.6 Resolution: 3840 x 2160 - Effects Quality: Ultimate Frames Per Second > Higher Is Better a . 311.40 |=================================================================== b . 311.77 |=================================================================== nekRS 23.0 Input: Kershaw flops/rank > Higher Is Better a . 2123046667 |=============================================================== b . 2109640000 |=============================================================== nekRS 23.0 Input: TurboPipe Periodic flops/rank > Higher Is Better a . 3444566667 |=============================================================== b . 3441770000 |=============================================================== Neural Magic DeepSparse 1.5 Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better a . 28.88 |==================================================================== b . 28.92 |==================================================================== Neural Magic DeepSparse 1.5 Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better a . 552.28 |=================================================================== b . 551.16 |=================================================================== Neural Magic DeepSparse 1.5 Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Stream items/sec > Higher Is Better a . 16.35 |=================================================================== b . 16.48 |==================================================================== Neural Magic DeepSparse 1.5 Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Stream ms/batch < Lower Is Better a . 61.17 |==================================================================== b . 60.66 |=================================================================== Neural Magic DeepSparse 1.5 Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better a . 255.99 |=================================================================== b . 256.64 |=================================================================== Neural Magic DeepSparse 1.5 Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better a . 62.44 |==================================================================== b . 62.31 |==================================================================== Neural Magic DeepSparse 1.5 Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Synchronous Single-Stream items/sec > Higher Is Better a . 77.58 |=================================================================== b . 78.40 |==================================================================== Neural Magic DeepSparse 1.5 Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Synchronous Single-Stream ms/batch < Lower Is Better a . 12.88 |==================================================================== b . 12.75 |=================================================================== Neural Magic DeepSparse 1.5 Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better a . 86.13 |=================================================================== b . 87.02 |==================================================================== Neural Magic DeepSparse 1.5 Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better a . 185.74 |=================================================================== b . 183.81 |================================================================== Neural Magic DeepSparse 1.5 Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Synchronous Single-Stream items/sec > Higher Is Better a . 28.73 |================================================================= b . 29.86 |==================================================================== Neural Magic DeepSparse 1.5 Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Synchronous Single-Stream ms/batch < Lower Is Better a . 34.80 |==================================================================== b . 33.48 |================================================================= Neural Magic DeepSparse 1.5 Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better a . 148.97 |=================================================================== b . 149.96 |=================================================================== Neural Magic DeepSparse 1.5 Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better a . 107.37 |=================================================================== b . 106.66 |=================================================================== Neural Magic DeepSparse 1.5 Model: CV Detection, YOLOv5s COCO - Scenario: Synchronous Single-Stream items/sec > Higher Is Better a . 91.57 |==================================================================== b . 91.98 |==================================================================== Neural Magic DeepSparse 1.5 Model: CV Detection, YOLOv5s COCO - Scenario: Synchronous Single-Stream ms/batch < Lower Is Better a . 10.91 |==================================================================== b . 10.86 |==================================================================== Neural Magic DeepSparse 1.5 Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better a . 323.09 |=================================================================== b . 324.27 |=================================================================== Neural Magic DeepSparse 1.5 Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better a . 49.49 |==================================================================== b . 49.32 |==================================================================== Neural Magic DeepSparse 1.5 Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Stream items/sec > Higher Is Better a . 141.30 |================================================================= b . 146.19 |=================================================================== Neural Magic DeepSparse 1.5 Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Stream ms/batch < Lower Is Better a . 7.0704 |=================================================================== b . 6.8330 |================================================================= Neural Magic DeepSparse 1.5 Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better a . 235.81 |=================================================================== b . 236.82 |=================================================================== Neural Magic DeepSparse 1.5 Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better a . 67.82 |==================================================================== b . 67.54 |==================================================================== Neural Magic DeepSparse 1.5 Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Stream items/sec > Higher Is Better a . 81.34 |================================================================== b . 83.43 |==================================================================== Neural Magic DeepSparse 1.5 Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Stream ms/batch < Lower Is Better a . 12.29 |==================================================================== b . 11.98 |================================================================== Neural Magic DeepSparse 1.5 Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better a . 33.10 |==================================================================== b . 32.91 |==================================================================== Neural Magic DeepSparse 1.5 Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better a . 482.75 |=================================================================== b . 485.95 |=================================================================== Neural Magic DeepSparse 1.5 Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Synchronous Single-Stream items/sec > Higher Is Better a . 21.57 |==================================================================== b . 21.49 |==================================================================== Neural Magic DeepSparse 1.5 Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Synchronous Single-Stream ms/batch < Lower Is Better a . 46.35 |==================================================================== b . 46.51 |==================================================================== Neural Magic DeepSparse 1.5 Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better a . 119.01 |=================================================================== b . 119.09 |=================================================================== Neural Magic DeepSparse 1.5 Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better a . 134.41 |=================================================================== b . 134.32 |=================================================================== Neural Magic DeepSparse 1.5 Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Synchronous Single-Stream items/sec > Higher Is Better a . 43.88 |==================================================================== b . 43.05 |=================================================================== Neural Magic DeepSparse 1.5 Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Synchronous Single-Stream ms/batch < Lower Is Better a . 22.78 |=================================================================== b . 23.22 |==================================================================== Neural Magic DeepSparse 1.5 Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better a . 28.61 |=================================================================== b . 28.99 |==================================================================== Neural Magic DeepSparse 1.5 Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better a . 556.61 |=================================================================== b . 550.43 |================================================================== Neural Magic DeepSparse 1.5 Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Stream items/sec > Higher Is Better a . 16.34 |==================================================================== b . 16.43 |==================================================================== Neural Magic DeepSparse 1.5 Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Stream ms/batch < Lower Is Better a . 61.20 |==================================================================== b . 60.86 |==================================================================== Whisper.cpp 1.4 Model: ggml-base.en - Input: 2016 State of the Union Seconds < Lower Is Better a . 156.48 |=================================================================== b . 151.05 |================================================================= Whisper.cpp 1.4 Model: ggml-small.en - Input: 2016 State of the Union Seconds < Lower Is Better a . 395.71 |=================================================================== b . 363.32 |============================================================== Whisper.cpp 1.4 Model: ggml-medium.en - Input: 2016 State of the Union Seconds < Lower Is Better a . 1018.28 |================================================================== b . 1003.11 |================================================================= High Performance Conjugate Gradient 3.1 X Y Z: 104 104 104 - RT: 60 GFLOP/s > Higher Is Better a . 10.96 |==================================================================== b . 11.02 |==================================================================== High Performance Conjugate Gradient 3.1 X Y Z: 144 144 144 - RT: 60 GFLOP/s > Higher Is Better oneDNN 3.1 Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 1.55099 |================================================================== b . 1.30181 |======================================================= oneDNN 3.1 Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 4.26624 |================================================================== b . 4.21682 |================================================================= oneDNN 3.1 Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 1.177229 |================================================================= b . 1.089440 |============================================================ oneDNN 3.1 Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 0.948450 |=============================================================== b . 0.985098 |================================================================= oneDNN 3.1 Harness: IP Shapes 1D - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better oneDNN 3.1 Harness: IP Shapes 3D - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better oneDNN 3.1 Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 4.81893 |================================================================== b . 4.83565 |================================================================== oneDNN 3.1 Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 5.69206 |================================================================== b . 5.73181 |================================================================== oneDNN 3.1 Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 2.68566 |================================================================== b . 2.69872 |================================================================== oneDNN 3.1 Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 5.76769 |================================================================== b . 5.70574 |================================================================= oneDNN 3.1 Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 1.36630 |=============================================================== b . 1.43664 |================================================================== oneDNN 3.1 Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 1.57740 |================================================================== b . 1.57190 |================================================================== oneDNN 3.1 Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 3252.18 |================================================================== b . 3275.76 |================================================================== oneDNN 3.1 Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 976.47 |================================================================== b . 987.99 |=================================================================== oneDNN 3.1 Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 3244.46 |================================================================== b . 3227.02 |================================================================== oneDNN 3.1 Harness: Convolution Batch Shapes Auto - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better oneDNN 3.1 Harness: Deconvolution Batch shapes_1d - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better oneDNN 3.1 Harness: Deconvolution Batch shapes_3d - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better oneDNN 3.1 Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 938.10 |================================================================== b . 958.84 |=================================================================== oneDNN 3.1 Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better a . 3235.41 |================================================================== b . 3226.70 |================================================================== oneDNN 3.1 Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better a . 935.61 |=================================================================== b . 932.99 |=================================================================== Kripke 1.2.6 Throughput FoM > Higher Is Better a . 148243333 |================================================================ b . 146215600 |=============================================================== Monte Carlo Simulations of Ionised Nebulae 2.02.73.3 Input: Gas HII40 Seconds < Lower Is Better a . 12.68 |==================================================================== b . 12.60 |==================================================================== Monte Carlo Simulations of Ionised Nebulae 2.02.73.3 Input: Dust 2D tau100.0 Seconds < Lower Is Better a . 181.27 |=================================================================== b . 180.73 |=================================================================== QMCPACK 3.16 Input: Li2_STO_ae Total Execution Time - Seconds < Lower Is Better a . 136.22 |=================================================================== b . 132.76 |================================================================= QMCPACK 3.16 Input: simple-H2O Total Execution Time - Seconds < Lower Is Better a . 27.60 |==================================================================== b . 27.48 |==================================================================== QMCPACK 3.16 Input: FeCO6_b3lyp_gms Total Execution Time - Seconds < Lower Is Better a . 175.39 |=================================================================== b . 174.82 |=================================================================== QMCPACK 3.16 Input: FeCO6_b3lyp_gms Total Execution Time - Seconds < Lower Is Better a . 196.98 |=================================================================== b . 191.15 |================================================================= GPAW 23.6 Input: Carbon Nanotube Seconds < Lower Is Better a . 110.85 |=================================================================== b . 110.95 |=================================================================== CP2K Molecular Dynamics 2023.1 Input: H20-64 Seconds < Lower Is Better a . 42.97 |==================================================================== b . 42.11 |=================================================================== CP2K Molecular Dynamics 2023.1 Input: H2O-DFT-LS Seconds < Lower Is Better CP2K Molecular Dynamics 2023.1 Input: Fayalite-FIST Seconds < Lower Is Better a . 123.83 |=================================================================== b . 122.98 |=================================================================== dav1d 1.2.1 Video Input: Chimera 1080p FPS > Higher Is Better a . 398.39 |=================================================================== b . 398.20 |=================================================================== dav1d 1.2.1 Video Input: Summer Nature 4K FPS > Higher Is Better a . 222.52 |=================================================================== b . 222.24 |=================================================================== dav1d 1.2.1 Video Input: Summer Nature 1080p FPS > Higher Is Better a . 597.02 |=================================================================== b . 597.19 |=================================================================== dav1d 1.2.1 Video Input: Chimera 1080p 10-bit FPS > Higher Is Better a . 374.79 |=================================================================== b . 374.13 |=================================================================== SVT-AV1 1.6 Encoder Mode: Preset 4 - Input: Bosphorus 4K Frames Per Second > Higher Is Better a . 3.756 |==================================================================== b . 3.721 |=================================================================== SVT-AV1 1.6 Encoder Mode: Preset 8 - Input: Bosphorus 4K Frames Per Second > Higher Is Better a . 54.15 |=================================================================== b . 54.56 |==================================================================== SVT-AV1 1.6 Encoder Mode: Preset 12 - Input: Bosphorus 4K Frames Per Second > Higher Is Better a . 126.42 |================================================================== b . 127.68 |=================================================================== SVT-AV1 1.6 Encoder Mode: Preset 13 - Input: Bosphorus 4K Frames Per Second > Higher Is Better a . 127.14 |=================================================================== b . 127.68 |=================================================================== SVT-AV1 1.6 Encoder Mode: Preset 4 - Input: Bosphorus 1080p Frames Per Second > Higher Is Better a . 10.87 |==================================================================== b . 10.85 |==================================================================== SVT-AV1 1.6 Encoder Mode: Preset 8 - Input: Bosphorus 1080p Frames Per Second > Higher Is Better a . 85.31 |==================================================================== b . 85.50 |==================================================================== SVT-AV1 1.6 Encoder Mode: Preset 12 - Input: Bosphorus 1080p Frames Per Second > Higher Is Better a . 308.25 |=================================================================== b . 305.73 |================================================================== SVT-AV1 1.6 Encoder Mode: Preset 13 - Input: Bosphorus 1080p Frames Per Second > Higher Is Better a . 360.92 |================================================================== b . 364.28 |=================================================================== VVenC 1.8 Video Input: Bosphorus 4K - Video Preset: Fast Frames Per Second > Higher Is Better a . 5.440 |==================================================================== b . 5.387 |=================================================================== VVenC 1.8 Video Input: Bosphorus 4K - Video Preset: Faster Frames Per Second > Higher Is Better a . 10.93 |==================================================================== b . 10.89 |==================================================================== VVenC 1.8 Video Input: Bosphorus 1080p - Video Preset: Fast Frames Per Second > Higher Is Better a . 13.88 |==================================================================== b . 13.77 |=================================================================== VVenC 1.8 Video Input: Bosphorus 1080p - Video Preset: Faster Frames Per Second > Higher Is Better a . 24.88 |==================================================================== b . 24.80 |==================================================================== Embree 4.1 Binary: Pathtracer - Model: Crown Frames Per Second > Higher Is Better a . 38.47 |==================================================================== b . 38.45 |==================================================================== Embree 4.1 Binary: Pathtracer ISPC - Model: Crown Frames Per Second > Higher Is Better a . 34.41 |==================================================================== b . 34.53 |==================================================================== Embree 4.1 Binary: Pathtracer - Model: Asian Dragon Frames Per Second > Higher Is Better a . 41.59 |==================================================================== b . 41.78 |==================================================================== Embree 4.1 Binary: Pathtracer - Model: Asian Dragon Obj Frames Per Second > Higher Is Better a . 37.39 |==================================================================== b . 37.48 |==================================================================== Embree 4.1 Binary: Pathtracer ISPC - Model: Asian Dragon Frames Per Second > Higher Is Better a . 39.40 |==================================================================== b . 39.40 |==================================================================== Embree 4.1 Binary: Pathtracer ISPC - Model: Asian Dragon Obj Frames Per Second > Higher Is Better a . 33.83 |==================================================================== b . 33.96 |==================================================================== Intel Open Image Denoise 2.0 Run: RT.hdr_alb_nrm.3840x2160 - Device: CPU-Only Images / Sec > Higher Is Better a . 1.22 |===================================================================== b . 1.22 |===================================================================== Intel Open Image Denoise 2.0 Run: RT.ldr_alb_nrm.3840x2160 - Device: CPU-Only Images / Sec > Higher Is Better a . 1.22 |==================================================================== b . 1.23 |===================================================================== Intel Open Image Denoise 2.0 Run: RTLightmap.hdr.4096x4096 - Device: CPU-Only Images / Sec > Higher Is Better a . 0.60 |===================================================================== b . 0.60 |===================================================================== Intel Open Image Denoise 2.0 Run: RT.hdr_alb_nrm.3840x2160 - Device: Radeon HIP Images / Sec > Higher Is Better Intel Open Image Denoise 2.0 Run: RT.ldr_alb_nrm.3840x2160 - Device: Radeon HIP Images / Sec > Higher Is Better Intel Open Image Denoise 2.0 Run: RTLightmap.hdr.4096x4096 - Device: Radeon HIP Images / Sec > Higher Is Better Intel Open Image Denoise 2.0 Run: RT.hdr_alb_nrm.3840x2160 - Device: Intel oneAPI SYCL Images / Sec > Higher Is Better Intel Open Image Denoise 2.0 Run: RT.ldr_alb_nrm.3840x2160 - Device: Intel oneAPI SYCL Images / Sec > Higher Is Better Intel Open Image Denoise 2.0 Run: RTLightmap.hdr.4096x4096 - Device: Intel oneAPI SYCL Images / Sec > Higher Is Better OSPRay 2.12 Benchmark: particle_volume/ao/real_time Items Per Second > Higher Is Better a . 9.86893 |================================================================== b . 9.89124 |================================================================== OSPRay 2.12 Benchmark: particle_volume/scivis/real_time Items Per Second > Higher Is Better a . 9.74548 |================================================================== b . 9.76771 |================================================================== OSPRay 2.12 Benchmark: particle_volume/pathtracer/real_time Items Per Second > Higher Is Better a . 128.57 |=================================================================== b . 128.66 |=================================================================== OSPRay 2.12 Benchmark: gravity_spheres_volume/dim_512/ao/real_time Items Per Second > Higher Is Better a . 4.93554 |================================================================= b . 4.98028 |================================================================== OSPRay 2.12 Benchmark: gravity_spheres_volume/dim_512/scivis/real_time Items Per Second > Higher Is Better a . 4.62468 |================================================================== b . 4.62434 |================================================================== OSPRay 2.12 Benchmark: gravity_spheres_volume/dim_512/pathtracer/real_time Items Per Second > Higher Is Better a . 7.67668 |================================================================== b . 7.70051 |================================================================== Liquid-DSP 1.6 Threads: 1 - Buffer Length: 256 - Filter Length: 32 samples/s > Higher Is Better a . 45075000 |================================================================= b . 45023000 |================================================================= Liquid-DSP 1.6 Threads: 1 - Buffer Length: 256 - Filter Length: 57 samples/s > Higher Is Better a . 51993333 |================================================================= b . 51814000 |================================================================= Liquid-DSP 1.6 Threads: 2 - Buffer Length: 256 - Filter Length: 32 samples/s > Higher Is Better a . 89896333 |================================================================= b . 89686000 |================================================================= Liquid-DSP 1.6 Threads: 2 - Buffer Length: 256 - Filter Length: 57 samples/s > Higher Is Better a . 103806667 |================================================================ b . 103260000 |================================================================ Liquid-DSP 1.6 Threads: 4 - Buffer Length: 256 - Filter Length: 32 samples/s > Higher Is Better a . 178100000 |================================================================ b . 179170000 |================================================================ Liquid-DSP 1.6 Threads: 4 - Buffer Length: 256 - Filter Length: 57 samples/s > Higher Is Better a . 206086667 |================================================================ b . 206140000 |================================================================ Liquid-DSP 1.6 Threads: 8 - Buffer Length: 256 - Filter Length: 32 samples/s > Higher Is Better a . 354570000 |================================================================ b . 355110000 |================================================================ Liquid-DSP 1.6 Threads: 8 - Buffer Length: 256 - Filter Length: 57 samples/s > Higher Is Better a . 409183333 |================================================================ b . 410090000 |================================================================ Liquid-DSP 1.6 Threads: 1 - Buffer Length: 256 - Filter Length: 512 samples/s > Higher Is Better a . 10537667 |================================================================= b . 10560000 |================================================================= Liquid-DSP 1.6 Threads: 16 - Buffer Length: 256 - Filter Length: 32 samples/s > Higher Is Better a . 690800000 |================================================================ b . 692130000 |================================================================ Liquid-DSP 1.6 Threads: 16 - Buffer Length: 256 - Filter Length: 57 samples/s > Higher Is Better a . 795103333 |================================================================ b . 799490000 |================================================================ Liquid-DSP 1.6 Threads: 2 - Buffer Length: 256 - Filter Length: 512 samples/s > Higher Is Better a . 20851667 |================================================================= b . 20989000 |================================================================= Liquid-DSP 1.6 Threads: 32 - Buffer Length: 256 - Filter Length: 32 samples/s > Higher Is Better a . 1343200000 |=============================================================== b . 1350000000 |=============================================================== Liquid-DSP 1.6 Threads: 32 - Buffer Length: 256 - Filter Length: 57 samples/s > Higher Is Better a . 1506266667 |=============================================================== b . 1512100000 |=============================================================== Liquid-DSP 1.6 Threads: 4 - Buffer Length: 256 - Filter Length: 512 samples/s > Higher Is Better a . 41277667 |================================================================= b . 41475000 |================================================================= Liquid-DSP 1.6 Threads: 64 - Buffer Length: 256 - Filter Length: 32 samples/s > Higher Is Better a . 2250733333 |============================================================== b . 2269700000 |=============================================================== Liquid-DSP 1.6 Threads: 64 - Buffer Length: 256 - Filter Length: 57 samples/s > Higher Is Better a . 1836033333 |=============================================================== b . 1837000000 |=============================================================== Liquid-DSP 1.6 Threads: 8 - Buffer Length: 256 - Filter Length: 512 samples/s > Higher Is Better a . 82123667 |================================================================= b . 82224000 |================================================================= Liquid-DSP 1.6 Threads: 16 - Buffer Length: 256 - Filter Length: 512 samples/s > Higher Is Better a . 160113333 |================================================================ b . 160130000 |================================================================ Liquid-DSP 1.6 Threads: 32 - Buffer Length: 256 - Filter Length: 512 samples/s > Higher Is Better a . 313753333 |================================================================ b . 314560000 |================================================================ Liquid-DSP 1.6 Threads: 64 - Buffer Length: 256 - Filter Length: 512 samples/s > Higher Is Better a . 506326667 |================================================================ b . 506050000 |================================================================ SQLite 3.41.2 Threads / Copies: 1 Seconds < Lower Is Better a . 106.01 |=================================================================== b . 105.00 |================================================================== SQLite 3.41.2 Threads / Copies: 2 Seconds < Lower Is Better a . 243.22 |=================================================================== b . 237.19 |================================================================= SQLite 3.41.2 Threads / Copies: 4 Seconds < Lower Is Better a . 266.58 |=================================================================== b . 262.62 |================================================================== SQLite 3.41.2 Threads / Copies: 8 Seconds < Lower Is Better a . 291.25 |=================================================================== b . 284.87 |================================================================== SQLite 3.41.2 Threads / Copies: 16 Seconds < Lower Is Better a . 373.82 |=================================================================== b . 374.33 |=================================================================== SQLite 3.41.2 Threads / Copies: 32 Seconds < Lower Is Better a . 505.42 |=================================================================== b . 502.77 |=================================================================== SQLite 3.41.2 Threads / Copies: 64 Seconds < Lower Is Better a . 681.45 |=================================================================== b . 680.81 |=================================================================== LevelDB 1.23 Benchmark: Hot Read Microseconds Per Op < Lower Is Better a . 43.14 |==================================================================== b . 42.76 |=================================================================== LevelDB 1.23 Benchmark: Fill Sync Microseconds Per Op < Lower Is Better a . 10866.01 |=========================================== b . 16348.37 |================================================================= LevelDB 1.23 Benchmark: Overwrite MB/s > Higher Is Better a . 27.0 |===================================================================== b . 27.0 |===================================================================== PETSc 3.19 Test: Streams MB/s > Higher Is Better a . 58312.10 |================================================================= b . 58276.79 |================================================================= LevelDB 1.23 Benchmark: Fill Sync MB/s > Higher Is Better a . 0.6 |====================================================================== b . 0.4 |=============================================== LevelDB 1.23 Benchmark: Overwrite Microseconds Per Op < Lower Is Better a . 262.35 |=================================================================== b . 262.28 |=================================================================== LevelDB 1.23 Benchmark: Random Fill MB/s > Higher Is Better a . 26.9 |===================================================================== b . 26.7 |==================================================================== LevelDB 1.23 Benchmark: Random Fill Microseconds Per Op < Lower Is Better a . 262.98 |=================================================================== b . 264.87 |=================================================================== LevelDB 1.23 Benchmark: Random Read Microseconds Per Op < Lower Is Better a . 43.49 |==================================================================== b . 43.55 |==================================================================== LevelDB 1.23 Benchmark: Seek Random Microseconds Per Op < Lower Is Better a . 65.84 |==================================================================== b . 64.56 |=================================================================== LevelDB 1.23 Benchmark: Random Delete Microseconds Per Op < Lower Is Better a . 245.16 |=================================================================== b . 245.18 |=================================================================== LevelDB 1.23 Benchmark: Sequential Fill MB/s > Higher Is Better a . 27.8 |===================================================================== b . 27.7 |===================================================================== LevelDB 1.23 Benchmark: Sequential Fill Microseconds Per Op < Lower Is Better a . 254.94 |=================================================================== b . 255.49 |===================================================================