AMD EPYC 9684X 3D V-Cache
AMD EPYC 9684X 96-Core testing with a AMD Titanite_4G (RTI1007B BIOS) and ASPEED on Ubuntu 22.04 via the Phoronix Test Suite.


Default: 

	Processor: AMD EPYC 9684X 96-Core @ 2.55GHz (96 Cores / 192 Threads), Motherboard: AMD Titanite_4G (RTI1007B BIOS), Chipset: AMD Device 14a4, Memory: 768GB, Disk: 2 x 1920GB SAMSUNG MZWLJ1T9HBJR-00007, Graphics: ASPEED, Network: Broadcom NetXtreme BCM5720 PCIe

	OS: Ubuntu 22.04, Kernel: 5.19.0-41-generic (x86_64), Desktop: GNOME Shell 42.5, Display Server: X Server 1.21.1.4, Vulkan: 1.3.224, Compiler: GCC 11.3.0, File-System: ext4, Screen Resolution: 1024x768


Stress-NG 0.15.10
Test: x86_64 RdRand


Stress-NG 0.15.10
Test: Hash
Bogo Ops/s > Higher Is Better
Default . 18746640.55 |========================================================


Stress-NG 0.15.10
Test: MMAP
Bogo Ops/s > Higher Is Better
Default . 1444.92 |============================================================


Stress-NG 0.15.10
Test: NUMA
Bogo Ops/s > Higher Is Better
Default . 2478.54 |============================================================


Stress-NG 0.15.10
Test: Pipe
Bogo Ops/s > Higher Is Better
Default . 60302912.67 |========================================================


Stress-NG 0.15.10
Test: Poll
Bogo Ops/s > Higher Is Better
Default . 13269096.62 |========================================================


Stress-NG 0.15.10
Test: Zlib
Bogo Ops/s > Higher Is Better
Default . 10471.17 |===========================================================


Stress-NG 0.15.10
Test: Futex
Bogo Ops/s > Higher Is Better
Default . 3985709.56 |=========================================================


Stress-NG 0.15.10
Test: MEMFD
Bogo Ops/s > Higher Is Better
Default . 454.75 |=============================================================


Stress-NG 0.15.10
Test: Mutex
Bogo Ops/s > Higher Is Better
Default . 49736118.06 |========================================================


Stress-NG 0.15.10
Test: Atomic
Bogo Ops/s > Higher Is Better
Default . 237.83 |=============================================================


Stress-NG 0.15.10
Test: Crypto
Bogo Ops/s > Higher Is Better
Default . 202368.61 |==========================================================


Stress-NG 0.15.10
Test: Malloc
Bogo Ops/s > Higher Is Better
Default . 360348999.65 |=======================================================


Stress-NG 0.15.10
Test: Cloning
Bogo Ops/s > Higher Is Better
Default . 12478.74 |===========================================================


Stress-NG 0.15.10
Test: Forking
Bogo Ops/s > Higher Is Better
Default . 40400.83 |===========================================================


Stress-NG 0.15.10
Test: Pthread
Bogo Ops/s > Higher Is Better
Default . 103280.79 |==========================================================


Stress-NG 0.15.10
Test: AVL Tree
Bogo Ops/s > Higher Is Better
Default . 1665.57 |============================================================


Stress-NG 0.15.10
Test: IO_uring
Bogo Ops/s > Higher Is Better
Default . 4790428.16 |=========================================================


Stress-NG 0.15.10
Test: SENDFILE
Bogo Ops/s > Higher Is Better
Default . 1517063.84 |=========================================================


Stress-NG 0.15.10
Test: CPU Cache
Bogo Ops/s > Higher Is Better
Default . 1397574.75 |=========================================================


Stress-NG 0.15.10
Test: CPU Stress
Bogo Ops/s > Higher Is Better
Default . 212380.76 |==========================================================


Stress-NG 0.15.10
Test: Semaphores
Bogo Ops/s > Higher Is Better
Default . 223213939.86 |=======================================================


Stress-NG 0.15.10
Test: Matrix Math
Bogo Ops/s > Higher Is Better
Default . 418033.13 |==========================================================


Stress-NG 0.15.10
Test: Vector Math
Bogo Ops/s > Higher Is Better
Default . 545725.73 |==========================================================


Stress-NG 0.15.10
Test: Function Call
Bogo Ops/s > Higher Is Better
Default . 67313.39 |===========================================================


Stress-NG 0.15.10
Test: Floating Point
Bogo Ops/s > Higher Is Better
Default . 29883.93 |===========================================================


Stress-NG 0.15.10
Test: Matrix 3D Math
Bogo Ops/s > Higher Is Better
Default . 16595.28 |===========================================================


Stress-NG 0.15.10
Test: Memory Copying
Bogo Ops/s > Higher Is Better
Default . 32994.18 |===========================================================


Stress-NG 0.15.10
Test: Vector Shuffle
Bogo Ops/s > Higher Is Better
Default . 63761.29 |===========================================================


Stress-NG 0.15.10
Test: Socket Activity
Bogo Ops/s > Higher Is Better
Default . 2960.24 |============================================================


Stress-NG 0.15.10
Test: Wide Vector Math
Bogo Ops/s > Higher Is Better
Default . 3485374.33 |=========================================================


Stress-NG 0.15.10
Test: Context Switching
Bogo Ops/s > Higher Is Better
Default . 15480601.67 |========================================================


Stress-NG 0.15.10
Test: Fused Multiply-Add
Bogo Ops/s > Higher Is Better
Default . 76566577.12 |========================================================


Stress-NG 0.15.10
Test: Vector Floating Point
Bogo Ops/s > Higher Is Better
Default . 257925.61 |==========================================================


Stress-NG 0.15.10
Test: Glibc C String Functions
Bogo Ops/s > Higher Is Better
Default . 81208060.17 |========================================================


Stress-NG 0.15.10
Test: Glibc Qsort Data Sorting
Bogo Ops/s > Higher Is Better
Default . 2108.30 |============================================================


Stress-NG 0.15.10
Test: System V Message Passing
Bogo Ops/s > Higher Is Better
Default . 12085427.22 |========================================================


miniFE 2.2
Problem Size: Small
CG Mflops > Higher Is Better
Default . 54408.2 |============================================================


Algebraic Multi-Grid Benchmark 1.2

Figure Of Merit > Higher Is Better
Default . 2414283000 |=========================================================


OpenVINO 2022.3
Model: Face Detection FP16 - Device: CPU
FPS > Higher Is Better
Default . 47.62 |==============================================================


OpenVINO 2022.3
Model: Person Detection FP16 - Device: CPU
FPS > Higher Is Better
Default . 27.11 |==============================================================


OpenVINO 2022.3
Model: Person Detection FP32 - Device: CPU
FPS > Higher Is Better
Default . 26.89 |==============================================================


OpenVINO 2022.3
Model: Vehicle Detection FP16 - Device: CPU
FPS > Higher Is Better
Default . 3860.64 |============================================================


OpenVINO 2022.3
Model: Face Detection FP16-INT8 - Device: CPU
FPS > Higher Is Better
Default . 90.36 |==============================================================


OpenVINO 2022.3
Model: Vehicle Detection FP16-INT8 - Device: CPU
FPS > Higher Is Better
Default . 5672.06 |============================================================


OpenVINO 2022.3
Model: Weld Porosity Detection FP16 - Device: CPU
FPS > Higher Is Better
Default . 4663.97 |============================================================


OpenVINO 2022.3
Model: Machine Translation EN To DE FP16 - Device: CPU
FPS > Higher Is Better
Default . 535.77 |=============================================================


OpenVINO 2022.3
Model: Weld Porosity Detection FP16-INT8 - Device: CPU
FPS > Higher Is Better
Default . 8846.67 |============================================================


OpenVINO 2022.3
Model: Person Vehicle Bike Detection FP16 - Device: CPU
FPS > Higher Is Better
Default . 5732.75 |============================================================


OpenVINO 2022.3
Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU
FPS > Higher Is Better
Default . 94505.11 |===========================================================


OpenVINO 2022.3
Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU
FPS > Higher Is Better
Default . 64461.93 |===========================================================


Embree 4.1
Binary: Pathtracer ISPC - Model: Crown
Frames Per Second > Higher Is Better
Default . 117.83 |=============================================================


Embree 4.1
Binary: Pathtracer ISPC - Model: Asian Dragon
Frames Per Second > Higher Is Better
Default . 144.00 |=============================================================


Embree 4.1
Binary: Pathtracer ISPC - Model: Asian Dragon Obj
Frames Per Second > Higher Is Better
Default . 123.51 |=============================================================


High Performance Conjugate Gradient 3.1
X Y Z: 104 104 104 - RT: 60
GFLOP/s > Higher Is Better
Default . 26.83 |==============================================================


High Performance Conjugate Gradient 3.1
X Y Z: 144 144 144 - RT: 60
GFLOP/s > Higher Is Better
Default . 24.61 |==============================================================


High Performance Conjugate Gradient 3.1
X Y Z: 160 160 160 - RT: 60
GFLOP/s > Higher Is Better
Default . 23.84 |==============================================================


High Performance Conjugate Gradient 3.1
X Y Z: 192 192 192 - RT: 60
GFLOP/s > Higher Is Better
Default . 22.83 |==============================================================


HeFFTe - Highly Efficient FFT for Exascale 2.3
Test: c2c - Backend: FFTW - Precision: float - X Y Z: 128
GFLOP/s > Higher Is Better
Default . 126.03 |=============================================================


HeFFTe - Highly Efficient FFT for Exascale 2.3
Test: c2c - Backend: FFTW - Precision: float - X Y Z: 256
GFLOP/s > Higher Is Better
Default . 178.44 |=============================================================


HeFFTe - Highly Efficient FFT for Exascale 2.3
Test: c2c - Backend: FFTW - Precision: float - X Y Z: 512
GFLOP/s > Higher Is Better
Default . 153.84 |=============================================================


HeFFTe - Highly Efficient FFT for Exascale 2.3
Test: r2c - Backend: FFTW - Precision: float - X Y Z: 128
GFLOP/s > Higher Is Better
Default . 185.39 |=============================================================


HeFFTe - Highly Efficient FFT for Exascale 2.3
Test: r2c - Backend: FFTW - Precision: float - X Y Z: 256
GFLOP/s > Higher Is Better
Default . 315.81 |=============================================================


HeFFTe - Highly Efficient FFT for Exascale 2.3
Test: r2c - Backend: FFTW - Precision: float - X Y Z: 512
GFLOP/s > Higher Is Better
Default . 332.74 |=============================================================


HeFFTe - Highly Efficient FFT for Exascale 2.3
Test: c2c - Backend: FFTW - Precision: double - X Y Z: 128
GFLOP/s > Higher Is Better
Default . 79.92 |==============================================================


HeFFTe - Highly Efficient FFT for Exascale 2.3
Test: c2c - Backend: FFTW - Precision: double - X Y Z: 256
GFLOP/s > Higher Is Better
Default . 87.04 |==============================================================


HeFFTe - Highly Efficient FFT for Exascale 2.3
Test: c2c - Backend: FFTW - Precision: double - X Y Z: 512
GFLOP/s > Higher Is Better
Default . 67.85 |==============================================================


HeFFTe - Highly Efficient FFT for Exascale 2.3
Test: r2c - Backend: FFTW - Precision: double - X Y Z: 128
GFLOP/s > Higher Is Better
Default . 129.88 |=============================================================


HeFFTe - Highly Efficient FFT for Exascale 2.3
Test: r2c - Backend: FFTW - Precision: double - X Y Z: 256
GFLOP/s > Higher Is Better
Default . 190.13 |=============================================================


HeFFTe - Highly Efficient FFT for Exascale 2.3
Test: r2c - Backend: FFTW - Precision: double - X Y Z: 512
GFLOP/s > Higher Is Better
Default . 134.82 |=============================================================


ACES DGEMM 1.0
Sustained Floating-Point Rate
GFLOP/s > Higher Is Better
Default . 40.55 |==============================================================


libxsmm 2-1.17-3645
M N K: 128
GFLOPS/s > Higher Is Better
Default . 2913.4 |=============================================================


libxsmm 2-1.17-3645
M N K: 256
GFLOPS/s > Higher Is Better
Default . 3064.4 |=============================================================


libxsmm 2-1.17-3645
M N K: 32
GFLOPS/s > Higher Is Better
Default . 1311.3 |=============================================================


libxsmm 2-1.17-3645
M N K: 64
GFLOPS/s > Higher Is Better
Default . 2455.4 |=============================================================


Xmrig 6.18.1
Variant: Monero - Hash Count: 1M
H/s > Higher Is Better
Default . 69684.3 |============================================================


Xmrig 6.18.1
Variant: Wownero - Hash Count: 1M
H/s > Higher Is Better
Default . 74009.7 |============================================================


TensorFlow 2.12
Device: CPU - Batch Size: 16 - Model: AlexNet
images/sec > Higher Is Better
Default . 303.80 |=============================================================


TensorFlow 2.12
Device: CPU - Batch Size: 32 - Model: AlexNet
images/sec > Higher Is Better
Default . 518.15 |=============================================================


TensorFlow 2.12
Device: CPU - Batch Size: 64 - Model: AlexNet
images/sec > Higher Is Better
Default . 786.60 |=============================================================


TensorFlow 2.12
Device: CPU - Batch Size: 256 - Model: AlexNet
images/sec > Higher Is Better
Default . 1196.16 |============================================================


TensorFlow 2.12
Device: CPU - Batch Size: 512 - Model: AlexNet
images/sec > Higher Is Better
Default . 1287.81 |============================================================


TensorFlow 2.12
Device: CPU - Batch Size: 16 - Model: GoogLeNet
images/sec > Higher Is Better
Default . 156.94 |=============================================================


TensorFlow 2.12
Device: CPU - Batch Size: 16 - Model: ResNet-50
images/sec > Higher Is Better
Default . 57.21 |==============================================================


TensorFlow 2.12
Device: CPU - Batch Size: 32 - Model: GoogLeNet
images/sec > Higher Is Better
Default . 238.18 |=============================================================


TensorFlow 2.12
Device: CPU - Batch Size: 32 - Model: ResNet-50
images/sec > Higher Is Better
Default . 78.11 |==============================================================


TensorFlow 2.12
Device: CPU - Batch Size: 64 - Model: GoogLeNet
images/sec > Higher Is Better
Default . 296.19 |=============================================================


TensorFlow 2.12
Device: CPU - Batch Size: 64 - Model: ResNet-50
images/sec > Higher Is Better
Default . 94.50 |==============================================================


TensorFlow 2.12
Device: CPU - Batch Size: 256 - Model: GoogLeNet
images/sec > Higher Is Better
Default . 387.68 |=============================================================


TensorFlow 2.12
Device: CPU - Batch Size: 256 - Model: ResNet-50
images/sec > Higher Is Better
Default . 115.51 |=============================================================


TensorFlow 2.12
Device: CPU - Batch Size: 512 - Model: GoogLeNet
images/sec > Higher Is Better
Default . 409.02 |=============================================================


TensorFlow 2.12
Device: CPU - Batch Size: 512 - Model: ResNet-50
images/sec > Higher Is Better
Default . 116.15 |=============================================================


OSPRay 2.12
Benchmark: particle_volume/ao/real_time
Items Per Second > Higher Is Better
Default . 25.16 |==============================================================


OSPRay 2.12
Benchmark: particle_volume/scivis/real_time
Items Per Second > Higher Is Better
Default . 25.11 |==============================================================


OSPRay 2.12
Benchmark: particle_volume/pathtracer/real_time
Items Per Second > Higher Is Better
Default . 199.70 |=============================================================


OSPRay 2.12
Benchmark: gravity_spheres_volume/dim_512/ao/real_time
Items Per Second > Higher Is Better
Default . 26.79 |==============================================================


OSPRay 2.12
Benchmark: gravity_spheres_volume/dim_512/scivis/real_time
Items Per Second > Higher Is Better
Default . 25.93 |==============================================================


OSPRay 2.12
Benchmark: gravity_spheres_volume/dim_512/pathtracer/real_time
Items Per Second > Higher Is Better
Default . 26.51 |==============================================================


Neural Magic DeepSparse 1.5
Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream
items/sec > Higher Is Better
Default . 60.63 |==============================================================


Neural Magic DeepSparse 1.5
Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Asynchronous Multi-Stream
items/sec > Higher Is Better
Default . 1219.50 |============================================================


Neural Magic DeepSparse 1.5
Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Stream
items/sec > Higher Is Better
Default . 329.98 |=============================================================


Neural Magic DeepSparse 1.5
Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream
items/sec > Higher Is Better
Default . 344.41 |=============================================================


Neural Magic DeepSparse 1.5
Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream
items/sec > Higher Is Better
Default . 797.95 |=============================================================


Neural Magic DeepSparse 1.5
Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream
items/sec > Higher Is Better
Default . 513.19 |=============================================================


Neural Magic DeepSparse 1.5
Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream
items/sec > Higher Is Better
Default . 114.18 |=============================================================


Neural Magic DeepSparse 1.5
Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Stream
items/sec > Higher Is Better
Default . 257.57 |=============================================================


Neural Magic DeepSparse 1.5
Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream
items/sec > Higher Is Better
Default . 60.58 |==============================================================


ASKAP 1.0
Test: Hogbom Clean OpenMP
Iterations Per Second > Higher Is Better
Default . 1212.17 |============================================================


Laghos 3.1
Test: Triple Point Problem
Major Kernels Total Rate > Higher Is Better
Default . 238.89 |=============================================================


Laghos 3.1
Test: Sedov Blast Wave, ube_922_hex.mesh
Major Kernels Total Rate > Higher Is Better
Default . 446.93 |=============================================================


Zstd Compression 1.5.4
Compression Level: 3 - Compression Speed
MB/s > Higher Is Better
Default . 3989.7 |=============================================================


Zstd Compression 1.5.4
Compression Level: 3 - Decompression Speed
MB/s > Higher Is Better
Default . 1498.8 |=============================================================


Zstd Compression 1.5.4
Compression Level: 8 - Compression Speed
MB/s > Higher Is Better
Default . 1226.7 |=============================================================


Zstd Compression 1.5.4
Compression Level: 8 - Decompression Speed
MB/s > Higher Is Better
Default . 1639.9 |=============================================================


Zstd Compression 1.5.4
Compression Level: 12 - Compression Speed
MB/s > Higher Is Better
Default . 329.3 |==============================================================


Zstd Compression 1.5.4
Compression Level: 12 - Decompression Speed
MB/s > Higher Is Better
Default . 1653.3 |=============================================================


Zstd Compression 1.5.4
Compression Level: 19 - Compression Speed
MB/s > Higher Is Better
Default . 17.3 |===============================================================


Zstd Compression 1.5.4
Compression Level: 19 - Decompression Speed
MB/s > Higher Is Better
Default . 1433.4 |=============================================================


Zstd Compression 1.5.4
Compression Level: 3, Long Mode - Compression Speed
MB/s > Higher Is Better
Default . 889.9 |==============================================================


Zstd Compression 1.5.4
Compression Level: 3, Long Mode - Decompression Speed
MB/s > Higher Is Better
Default . 1534.5 |=============================================================


Zstd Compression 1.5.4
Compression Level: 8, Long Mode - Compression Speed
MB/s > Higher Is Better
Default . 876.9 |==============================================================


Zstd Compression 1.5.4
Compression Level: 8, Long Mode - Decompression Speed
MB/s > Higher Is Better
Default . 1648.1 |=============================================================


Zstd Compression 1.5.4
Compression Level: 19, Long Mode - Compression Speed
MB/s > Higher Is Better
Default . 8.52 |===============================================================


Zstd Compression 1.5.4
Compression Level: 19, Long Mode - Decompression Speed
MB/s > Higher Is Better
Default . 1357.8 |=============================================================


PETSc 3.19
Test: Streams
MB/s > Higher Is Better
Default . 272616.80 |==========================================================


srsRAN Project 23.5
Test: Downlink Processor Benchmark
Mbps > Higher Is Better
Default . 721.3 |==============================================================


srsRAN Project 23.5
Test: PUSCH Processor Benchmark, Throughput Total
Mbps > Higher Is Better
Default . 18408.1 |============================================================


Palabos 2.3
Grid Size: 100
Mega Site Updates Per Second > Higher Is Better
Default . 591.53 |=============================================================


Palabos 2.3
Grid Size: 400
Mega Site Updates Per Second > Higher Is Better
Default . 317.82 |=============================================================


Palabos 2.3
Grid Size: 500
Mega Site Updates Per Second > Higher Is Better
Default . 328.71 |=============================================================


Palabos 2.3
Grid Size: 1000
Mega Site Updates Per Second > Higher Is Better
Default . 370.19 |=============================================================


ASKAP 1.0
Test: tConvolve MT - Gridding
Million Grid Points Per Second > Higher Is Better
Default . 13582.8 |============================================================


ASKAP 1.0
Test: tConvolve MT - Degridding
Million Grid Points Per Second > Higher Is Better
Default . 15603.2 |============================================================


ASKAP 1.0
Test: tConvolve OpenMP - Gridding
Million Grid Points Per Second > Higher Is Better
Default . 26625.6 |============================================================


ASKAP 1.0
Test: tConvolve OpenMP - Degridding
Million Grid Points Per Second > Higher Is Better
Default . 55153.0 |============================================================


7-Zip Compression 22.01
Test: Compression Rating
MIPS > Higher Is Better
Default . 647063 |=============================================================


7-Zip Compression 22.01
Test: Decompression Rating
MIPS > Higher Is Better
Default . 626472 |=============================================================


ASKAP 1.0
Test: tConvolve MPI - Degridding
Mpix/sec > Higher Is Better
Default . 59791.1 |============================================================


ASKAP 1.0
Test: tConvolve MPI - Gridding
Mpix/sec > Higher Is Better
Default . 73226.7 |============================================================


ASTC Encoder 4.0
Preset: Medium
MT/s > Higher Is Better
Default . 419.43 |=============================================================


ASTC Encoder 4.0
Preset: Thorough
MT/s > Higher Is Better
Default . 56.78 |==============================================================


ASTC Encoder 4.0
Preset: Exhaustive
MT/s > Higher Is Better
Default . 6.1411 |=============================================================


LeelaChessZero 0.28
Backend: BLAS
Nodes Per Second > Higher Is Better
Default . 9760 |===============================================================


LeelaChessZero 0.28
Backend: Eigen
Nodes Per Second > Higher Is Better
Default . 11884 |==============================================================


Stockfish 15
Total Time
Nodes Per Second > Higher Is Better
Default . 297289892 |==========================================================


asmFish 2018-07-23
1024 Hash Memory, 26 Depth
Nodes/second > Higher Is Better
Default . 234040870 |==========================================================


GROMACS 2023
Implementation: MPI CPU - Input: water_GMX50_bare
Ns Per Day > Higher Is Better
Default . 11.79 |==============================================================


LAMMPS Molecular Dynamics Simulator 23Jun2022
Model: 20k Atoms
ns/day > Higher Is Better
Default . 39.89 |==============================================================


Liquid-DSP 1.6
Threads: 64 - Buffer Length: 256 - Filter Length: 32
samples/s > Higher Is Better
Default . 2181266667 |=========================================================


Liquid-DSP 1.6
Threads: 64 - Buffer Length: 256 - Filter Length: 57
samples/s > Higher Is Better
Default . 2609466667 |=========================================================


Liquid-DSP 1.6
Threads: 128 - Buffer Length: 256 - Filter Length: 32
samples/s > Higher Is Better
Default . 3768733333 |=========================================================


Liquid-DSP 1.6
Threads: 128 - Buffer Length: 256 - Filter Length: 57
samples/s > Higher Is Better
Default . 3876733333 |=========================================================


Liquid-DSP 1.6
Threads: 192 - Buffer Length: 256 - Filter Length: 32
samples/s > Higher Is Better
Default . 4958533333 |=========================================================


Liquid-DSP 1.6
Threads: 192 - Buffer Length: 256 - Filter Length: 57
samples/s > Higher Is Better
Default . 4634633333 |=========================================================


Liquid-DSP 1.6
Threads: 64 - Buffer Length: 256 - Filter Length: 512
samples/s > Higher Is Better
Default . 727523333 |==========================================================


Liquid-DSP 1.6
Threads: 128 - Buffer Length: 256 - Filter Length: 512
samples/s > Higher Is Better
Default . 1081100000 |=========================================================


Liquid-DSP 1.6
Threads: 192 - Buffer Length: 256 - Filter Length: 512
samples/s > Higher Is Better
Default . 1287866667 |=========================================================


Numpy Benchmark

Score > Higher Is Better
Default . 586.50 |=============================================================


Kripke 1.2.6

Throughput FoM > Higher Is Better


NAS Parallel Benchmarks 3.4
Test / Class: BT.C
Total Mop/s > Higher Is Better
Default . 314777.90 |==========================================================


NAS Parallel Benchmarks 3.4
Test / Class: CG.C
Total Mop/s > Higher Is Better
Default . 59737.94 |===========================================================


NAS Parallel Benchmarks 3.4
Test / Class: EP.D
Total Mop/s > Higher Is Better
Default . 10697.90 |===========================================================


NAS Parallel Benchmarks 3.4
Test / Class: FT.C
Total Mop/s > Higher Is Better
Default . 118831.89 |==========================================================


NAS Parallel Benchmarks 3.4
Test / Class: IS.D
Total Mop/s > Higher Is Better
Default . 5696.51 |============================================================


NAS Parallel Benchmarks 3.4
Test / Class: LU.C
Total Mop/s > Higher Is Better
Default . 337910.64 |==========================================================


NAS Parallel Benchmarks 3.4
Test / Class: MG.C
Total Mop/s > Higher Is Better
Default . 137308.27 |==========================================================


NAS Parallel Benchmarks 3.4
Test / Class: SP.C
Total Mop/s > Higher Is Better
Default . 207614.70 |==========================================================


LULESH 2.0.3

z/s > Higher Is Better
Default . 30715.33 |===========================================================


NAMD 2.14
ATPase Simulation - 327,506 Atoms
days/ns < Lower Is Better
Default . 0.24733 |============================================================


OSPRay Studio 0.11
Camera: 1 - Resolution: 4K - Samples Per Pixel: 1 - Renderer: Path Tracer
ms < Lower Is Better
Default . 1059 |===============================================================


OSPRay Studio 0.11
Camera: 2 - Resolution: 4K - Samples Per Pixel: 1 - Renderer: Path Tracer
ms < Lower Is Better
Default . 1065 |===============================================================


OSPRay Studio 0.11
Camera: 3 - Resolution: 4K - Samples Per Pixel: 1 - Renderer: Path Tracer
ms < Lower Is Better
Default . 1261 |===============================================================


OSPRay Studio 0.11
Camera: 1 - Resolution: 4K - Samples Per Pixel: 16 - Renderer: Path Tracer
ms < Lower Is Better
Default . 16953 |==============================================================


OSPRay Studio 0.11
Camera: 1 - Resolution: 4K - Samples Per Pixel: 32 - Renderer: Path Tracer
ms < Lower Is Better
Default . 34007 |==============================================================


OSPRay Studio 0.11
Camera: 2 - Resolution: 4K - Samples Per Pixel: 16 - Renderer: Path Tracer
ms < Lower Is Better
Default . 17078 |==============================================================


OSPRay Studio 0.11
Camera: 2 - Resolution: 4K - Samples Per Pixel: 32 - Renderer: Path Tracer
ms < Lower Is Better
Default . 34341 |==============================================================


OSPRay Studio 0.11
Camera: 3 - Resolution: 4K - Samples Per Pixel: 16 - Renderer: Path Tracer
ms < Lower Is Better
Default . 20223 |==============================================================


OSPRay Studio 0.11
Camera: 3 - Resolution: 4K - Samples Per Pixel: 32 - Renderer: Path Tracer
ms < Lower Is Better
Default . 40392 |==============================================================


Google Draco 1.5.6
Model: Lion
ms < Lower Is Better
Default . 5011 |===============================================================


Google Draco 1.5.6
Model: Church Facade
ms < Lower Is Better
Default . 6043 |===============================================================


OpenVINO 2022.3
Model: Face Detection FP16 - Device: CPU
ms < Lower Is Better
Default . 1003.51 |============================================================


OpenVINO 2022.3
Model: Person Detection FP16 - Device: CPU
ms < Lower Is Better
Default . 1753.63 |============================================================


OpenVINO 2022.3
Model: Person Detection FP32 - Device: CPU
ms < Lower Is Better
Default . 1766.54 |============================================================


OpenVINO 2022.3
Model: Vehicle Detection FP16 - Device: CPU
ms < Lower Is Better
Default . 12.42 |==============================================================


OpenVINO 2022.3
Model: Face Detection FP16-INT8 - Device: CPU
ms < Lower Is Better
Default . 529.68 |=============================================================


OpenVINO 2022.3
Model: Vehicle Detection FP16-INT8 - Device: CPU
ms < Lower Is Better
Default . 8.45 |===============================================================


OpenVINO 2022.3
Model: Weld Porosity Detection FP16 - Device: CPU
ms < Lower Is Better
Default . 10.28 |==============================================================


OpenVINO 2022.3
Model: Machine Translation EN To DE FP16 - Device: CPU
ms < Lower Is Better
Default . 89.50 |==============================================================


OpenVINO 2022.3
Model: Weld Porosity Detection FP16-INT8 - Device: CPU
ms < Lower Is Better
Default . 10.84 |==============================================================


OpenVINO 2022.3
Model: Person Vehicle Bike Detection FP16 - Device: CPU
ms < Lower Is Better
Default . 8.36 |===============================================================


OpenVINO 2022.3
Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU
ms < Lower Is Better
Default . 0.84 |===============================================================


OpenVINO 2022.3
Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU
ms < Lower Is Better
Default . 1.33 |===============================================================


Neural Magic DeepSparse 1.5
Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream
ms/batch < Lower Is Better
Default . 783.58 |=============================================================


Neural Magic DeepSparse 1.5
Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Asynchronous Multi-Stream
ms/batch < Lower Is Better
Default . 39.31 |==============================================================


Neural Magic DeepSparse 1.5
Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Stream
ms/batch < Lower Is Better
Default . 145.05 |=============================================================


Neural Magic DeepSparse 1.5
Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream
ms/batch < Lower Is Better
Default . 139.02 |=============================================================


Neural Magic DeepSparse 1.5
Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream
ms/batch < Lower Is Better
Default . 60.06 |==============================================================


Neural Magic DeepSparse 1.5
Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream
ms/batch < Lower Is Better
Default . 93.32 |==============================================================


Neural Magic DeepSparse 1.5
Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream
ms/batch < Lower Is Better
Default . 417.86 |=============================================================


Neural Magic DeepSparse 1.5
Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Stream
ms/batch < Lower Is Better
Default . 185.85 |=============================================================


Neural Magic DeepSparse 1.5
Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream
ms/batch < Lower Is Better
Default . 785.21 |=============================================================


CloverLeaf
Lagrangian-Eulerian Hydrodynamics
Seconds < Lower Is Better
Default . 10.29 |==============================================================


Xcompact3d Incompact3d 2021-03-11
Input: input.i3d 129 Cells Per Direction
Seconds < Lower Is Better
Default . 2.17521613 |=========================================================


Xcompact3d Incompact3d 2021-03-11
Input: input.i3d 193 Cells Per Direction
Seconds < Lower Is Better
Default . 7.68528681 |=========================================================


Monte Carlo Simulations of Ionised Nebulae 2.02.73.3
Input: Gas HII40
Seconds < Lower Is Better
Default . 13.28 |==============================================================


Monte Carlo Simulations of Ionised Nebulae 2.02.73.3
Input: Dust 2D tau100.0
Seconds < Lower Is Better
Default . 190.07 |=============================================================


OpenFOAM 10
Input: drivaerFastback, Large Mesh Size - Mesh Time
Seconds < Lower Is Better
Default . 585.14 |=============================================================


OpenFOAM 10
Input: drivaerFastback, Large Mesh Size - Execution Time
Seconds < Lower Is Better
Default . 8994.47 |============================================================


OpenFOAM 10
Input: drivaerFastback, Small Mesh Size - Mesh Time
Seconds < Lower Is Better
Default . 22.97 |==============================================================


OpenFOAM 10
Input: drivaerFastback, Small Mesh Size - Execution Time
Seconds < Lower Is Better
Default . 29.88 |==============================================================


OpenFOAM 10
Input: drivaerFastback, Medium Mesh Size - Mesh Time
Seconds < Lower Is Better
Default . 108.37 |=============================================================


OpenFOAM 10
Input: drivaerFastback, Medium Mesh Size - Execution Time
Seconds < Lower Is Better
Default . 181.02 |=============================================================


Remhos 1.0
Test: Sample Remap Example
Seconds < Lower Is Better
Default . 10.29 |==============================================================


SPECFEM3D 4.0
Model: Mount St. Helens
Seconds < Lower Is Better
Default . 8.898145240 |========================================================


SPECFEM3D 4.0
Model: Layered Halfspace
Seconds < Lower Is Better
Default . 21.35 |==============================================================


SPECFEM3D 4.0
Model: Tomographic Model
Seconds < Lower Is Better
Default . 8.738903585 |========================================================


SPECFEM3D 4.0
Model: Homogeneous Halfspace
Seconds < Lower Is Better
Default . 11.32 |==============================================================


SPECFEM3D 4.0
Model: Water-layered Halfspace
Seconds < Lower Is Better
Default . 21.12 |==============================================================


Timed Gem5 Compilation 21.2
Time To Compile
Seconds < Lower Is Better
Default . 137.69 |=============================================================


Timed Godot Game Engine Compilation 4.0
Time To Compile
Seconds < Lower Is Better
Default . 88.38 |==============================================================


Timed Linux Kernel Compilation 6.1
Build: defconfig
Seconds < Lower Is Better
Default . 22.92 |==============================================================


Timed Linux Kernel Compilation 6.1
Build: allmodconfig
Seconds < Lower Is Better
Default . 202.56 |=============================================================


Timed LLVM Compilation 16.0
Build System: Ninja
Seconds < Lower Is Better
Default . 112.89 |=============================================================


Timed LLVM Compilation 16.0
Build System: Unix Makefiles
Seconds < Lower Is Better
Default . 184.05 |=============================================================


Timed Node.js Compilation 19.8.1
Time To Compile
Seconds < Lower Is Better
Default . 105.23 |=============================================================


Timed PHP Compilation 8.1.9
Time To Compile
Seconds < Lower Is Better
Default . 33.45 |==============================================================


Ngspice 34
Circuit: C2670
Seconds < Lower Is Better
Default . 118.39 |=============================================================


Ngspice 34
Circuit: C7552
Seconds < Lower Is Better
Default . 100.85 |=============================================================


WRF 4.2.2
Input: conus 2.5km
Seconds < Lower Is Better
Default . 11269.26 |===========================================================


GPAW 23.6
Input: Carbon Nanotube
Seconds < Lower Is Better
Default . 34.77 |==============================================================


Blender 3.6
Blend File: BMW27 - Compute: CPU-Only
Seconds < Lower Is Better
Default . 16.28 |==============================================================


Blender 3.6
Blend File: Classroom - Compute: CPU-Only
Seconds < Lower Is Better
Default . 40.51 |==============================================================


Blender 3.6
Blend File: Fishy Cat - Compute: CPU-Only
Seconds < Lower Is Better
Default . 20.62 |==============================================================


Blender 3.6
Blend File: Barbershop - Compute: CPU-Only
Seconds < Lower Is Better
Default . 142.03 |=============================================================


Blender 3.6
Blend File: Pabellon Barcelona - Compute: CPU-Only
Seconds < Lower Is Better
Default . 49.61 |==============================================================


PyHPC Benchmarks 3.0
Device: CPU - Backend: JAX - Project Size: 4194304 - Benchmark: Equation of State
Seconds < Lower Is Better


PyHPC Benchmarks 3.0
Device: CPU - Backend: JAX - Project Size: 4194304 - Benchmark: Isoneutral Mixing
Seconds < Lower Is Better


PyHPC Benchmarks 3.0
Device: CPU - Backend: Numba - Project Size: 4194304 - Benchmark: Equation of State
Seconds < Lower Is Better


PyHPC Benchmarks 3.0
Device: CPU - Backend: Numba - Project Size: 4194304 - Benchmark: Isoneutral Mixing
Seconds < Lower Is Better


PyHPC Benchmarks 3.0
Device: CPU - Backend: Numpy - Project Size: 4194304 - Benchmark: Equation of State
Seconds < Lower Is Better
Default . 0.767 |==============================================================


PyHPC Benchmarks 3.0
Device: CPU - Backend: Numpy - Project Size: 4194304 - Benchmark: Isoneutral Mixing
Seconds < Lower Is Better
Default . 1.578 |==============================================================


PyHPC Benchmarks 3.0
Device: CPU - Backend: Aesara - Project Size: 4194304 - Benchmark: Equation of State
Seconds < Lower Is Better


PyHPC Benchmarks 3.0
Device: CPU - Backend: Aesara - Project Size: 4194304 - Benchmark: Isoneutral Mixing
Seconds < Lower Is Better


PyHPC Benchmarks 3.0
Device: CPU - Backend: PyTorch - Project Size: 4194304 - Benchmark: Equation of State
Seconds < Lower Is Better


PyHPC Benchmarks 3.0
Device: CPU - Backend: PyTorch - Project Size: 4194304 - Benchmark: Isoneutral Mixing
Seconds < Lower Is Better


PyHPC Benchmarks 3.0
Device: CPU - Backend: TensorFlow - Project Size: 4194304 - Benchmark: Equation of State
Seconds < Lower Is Better


PyHPC Benchmarks 3.0
Device: CPU - Backend: TensorFlow - Project Size: 4194304 - Benchmark: Isoneutral Mixing
Seconds < Lower Is Better


Whisper.cpp 1.4
Model: ggml-base.en - Input: 2016 State of the Union
Seconds < Lower Is Better
Default . 332.02 |=============================================================


Whisper.cpp 1.4
Model: ggml-small.en - Input: 2016 State of the Union
Seconds < Lower Is Better
Default . 769.11 |=============================================================


Whisper.cpp 1.4
Model: ggml-medium.en - Input: 2016 State of the Union
Seconds < Lower Is Better
Default . 1444.14 |============================================================