new xeon

Intel Xeon Gold 6421N testing with a Quanta Cloud S6Q-MB-MPS (3A10.uh BIOS) and ASPEED on Ubuntu 22.04 via the Phoronix Test Suite.

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C++ Boost Tests 2 Tests
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July 30 2023
  5 Hours, 55 Minutes
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July 31 2023
  5 Hours, 22 Minutes
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new xeon Intel Xeon Gold 6421N testing with a Quanta Cloud S6Q-MB-MPS (3A10.uh BIOS) and ASPEED on Ubuntu 22.04 via the Phoronix Test Suite. ,,"a","b" Processor,,Intel Xeon Gold 6421N @ 3.60GHz (32 Cores / 64 Threads),Intel Xeon Gold 6421N @ 3.60GHz (32 Cores / 64 Threads) Motherboard,,Quanta Cloud S6Q-MB-MPS (3A10.uh BIOS),Quanta Cloud S6Q-MB-MPS (3A10.uh BIOS) Chipset,,Intel Device 1bce,Intel Device 1bce Memory,,512GB,512GB Disk,,3 x 3841GB Micron_9300_MTFDHAL3T8TDP,3 x 3841GB Micron_9300_MTFDHAL3T8TDP Graphics,,ASPEED,ASPEED Monitor,,VGA HDMI,VGA HDMI Network,,4 x Intel E810-C for QSFP,4 x Intel E810-C for QSFP OS,,Ubuntu 22.04,Ubuntu 22.04 Kernel,,5.15.0-47-generic (x86_64),5.15.0-47-generic (x86_64) Desktop,,GNOME Shell 42.4,GNOME Shell 42.4 Display Server,,X Server 1.21.1.3,X Server 1.21.1.3 Vulkan,,1.2.204,1.2.204 Compiler,,GCC 11.2.0,GCC 11.2.0 File-System,,ext4,ext4 Screen Resolution,,1600x1200,1600x1200 ,,"a","b" "Apache IoTDB - Device Count: 100 - Batch Size Per Write: 100 - Sensor Count: 200 (Latency)",HIB,31.83,43.86 "Apache IoTDB - Device Count: 100 - Batch Size Per Write: 100 - Sensor Count: 200 (point/sec)",HIB,43074031.84,34191814.86 "Stress-NG - Test: CPU Cache (Bogo Ops/s)",HIB,1537111.20,1885833.11 "libxsmm - M N K: 256 (GFLOPS/s)",HIB,879.6,758.9 "Apache IoTDB - Device Count: 200 - Batch Size Per Write: 100 - Sensor Count: 200 (Latency)",HIB,29.54,31.63 "Apache IoTDB - Device Count: 100 - Batch Size Per Write: 100 - Sensor Count: 500 (Latency)",HIB,69.08,73.56 "Apache IoTDB - Device Count: 500 - Batch Size Per Write: 1 - Sensor Count: 500 (Latency)",HIB,22.97,21.63 "HeFFTe - Highly Efficient FFT for Exascale - Test: c2c - Backend: Stock - Precision: double - X Y Z: 128 (GFLOP/s)",HIB,46.6357,49.5230 "Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,35.1529,37.3253 "Redis 7.0.12 + memtier_benchmark - Protocol: Redis - Clients: 100 - Set To Get Ratio: 1:10 (Ops/sec)",HIB,2447092.01,2304730.19 "Apache IoTDB - Device Count: 200 - Batch Size Per Write: 100 - Sensor Count: 200 (point/sec)",HIB,54224351.1,51199962.11 "Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,453.4802,428.6695 "Apache IoTDB - Device Count: 100 - Batch Size Per Write: 100 - Sensor Count: 500 (point/sec)",HIB,59041436.64,56018457.87 "Apache IoTDB - Device Count: 500 - Batch Size Per Write: 1 - Sensor Count: 500 (point/sec)",HIB,1916642.9,2009050.46 "Stress-NG - Test: Cloning (Bogo Ops/s)",HIB,9740.57,9326.09 "Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,137.3780,143.4387 "Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,116.3761,111.4976 "Apache IoTDB - Device Count: 500 - Batch Size Per Write: 1 - Sensor Count: 200 (Latency)",HIB,9.49,9.87 "HeFFTe - Highly Efficient FFT for Exascale - Test: r2c - Backend: Stock - Precision: float - X Y Z: 256 (GFLOP/s)",HIB,157.867,164.047 "Apache IoTDB - Device Count: 500 - Batch Size Per Write: 1 - Sensor Count: 200 (point/sec)",HIB,1576432.25,1521587.4 "HeFFTe - Highly Efficient FFT for Exascale - Test: c2c - Backend: FFTW - Precision: double - X Y Z: 128 (GFLOP/s)",HIB,64.4263,62.2974 "Stress-NG - Test: Futex (Bogo Ops/s)",HIB,1541676.36,1492979.46 "srsRAN Project - Test: PUSCH Processor Benchmark, Throughput Total (Mbps)",HIB,5372.9,5543.7 "Stress-NG - Test: Pipe (Bogo Ops/s)",HIB,35837711.85,36852791.12 "HeFFTe - Highly Efficient FFT for Exascale - Test: r2c - Backend: FFTW - Precision: float - X Y Z: 256 (GFLOP/s)",HIB,149.825,154.053 "Apache IoTDB - Device Count: 100 - Batch Size Per Write: 1 - Sensor Count: 200 (Latency)",HIB,14.58,14.98 "Apache IoTDB - Device Count: 200 - Batch Size Per Write: 1 - Sensor Count: 200 (Latency)",HIB,11.86,12.18 "Stress-NG - Test: SENDFILE (Bogo Ops/s)",HIB,582724.63,598173.56 "Redis 7.0.12 + memtier_benchmark - Protocol: Redis - Clients: 100 - Set To Get Ratio: 1:5 (Ops/sec)",HIB,2285996.17,2227152.02 "Stress-NG - Test: Matrix Math (Bogo Ops/s)",HIB,160653.44,156668.43 "Apache IoTDB - Device Count: 500 - Batch Size Per Write: 100 - Sensor Count: 500 (point/sec)",HIB,67607191.64,65935725.67 "Apache IoTDB - Device Count: 200 - Batch Size Per Write: 100 - Sensor Count: 500 (Latency)",HIB,101.25,98.87 "Apache IoTDB - Device Count: 200 - Batch Size Per Write: 1 - Sensor Count: 500 (point/sec)",HIB,1505080.34,1469808.89 "Apache IoTDB - Device Count: 200 - Batch Size Per Write: 100 - Sensor Count: 500 (point/sec)",HIB,45677447.24,46726912.46 "Liquid-DSP - Threads: 16 - Buffer Length: 256 - Filter Length: 512 (samples/s)",HIB,243940000,248820000 "Apache IoTDB - Device Count: 100 - Batch Size Per Write: 1 - Sensor Count: 200 (point/sec)",HIB,710382.44,697217.55 "Neural Magic DeepSparse - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,33.9358,34.5447 "Neural Magic DeepSparse - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,468.8046,460.6707 "srsRAN Project - Test: PUSCH Processor Benchmark, Throughput Thread (Mbps)",HIB,240.4,236.3 "Stress-NG - Test: IO_uring (Bogo Ops/s)",HIB,1529665.98,1503623.79 "Liquid-DSP - Threads: 16 - Buffer Length: 256 - Filter Length: 57 (samples/s)",HIB,848435000,862195000 "HeFFTe - Highly Efficient FFT for Exascale - Test: r2c - Backend: Stock - Precision: double - X Y Z: 128 (GFLOP/s)",HIB,92.3973,90.9851 "Neural Magic DeepSparse - Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,295.8295,299.9277 "Neural Magic DeepSparse - Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,54.0674,53.3291 "Apache IoTDB - Device Count: 500 - Batch Size Per Write: 100 - Sensor Count: 200 (point/sec)",HIB,56894390.61,56137174.7 "Stress-NG - Test: Socket Activity (Bogo Ops/s)",HIB,24947.14,25282.31 "Apache IoTDB - Device Count: 200 - Batch Size Per Write: 1 - Sensor Count: 500 (Latency)",HIB,26.29,26.64 "Liquid-DSP - Threads: 32 - Buffer Length: 256 - Filter Length: 512 (samples/s)",HIB,383555000,378650000 "VVenC - Video Input: Bosphorus 4K - Video Preset: Fast (FPS)",HIB,5.842,5.917 "Timed LLVM Compilation - Build System: Unix Makefiles (sec)",LIB,323.856,319.852 "HeFFTe - Highly Efficient FFT for Exascale - Test: r2c - Backend: Stock - Precision: float - X Y Z: 128 (GFLOP/s)",HIB,149.935,151.803 "Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,208.8471,211.2270 "Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,76.5807,75.7218 "libxsmm - M N K: 128 (GFLOPS/s)",HIB,1211.8,1225.0 "HeFFTe - Highly Efficient FFT for Exascale - Test: c2c - Backend: FFTW - Precision: double - X Y Z: 256 (GFLOP/s)",HIB,38.9304,38.5182 "libxsmm - M N K: 32 (GFLOPS/s)",HIB,440.0,444.6 "Redis 7.0.12 + memtier_benchmark - Protocol: Redis - Clients: 50 - Set To Get Ratio: 1:10 (Ops/sec)",HIB,2316281.26,2293467.62 "HeFFTe - Highly Efficient FFT for Exascale - Test: c2c - Backend: FFTW - Precision: float - X Y Z: 256 (GFLOP/s)",HIB,76.0299,75.3001 "VVenC - Video Input: Bosphorus 1080p - Video Preset: Fast (FPS)",HIB,16.100,16.249 "Stress-NG - Test: Atomic (Bogo Ops/s)",HIB,133.83,132.61 "Stress-NG - Test: Semaphores (Bogo Ops/s)",HIB,62126446.21,61651485.43 "HeFFTe - Highly Efficient FFT for Exascale - Test: c2c - Backend: Stock - Precision: double - X Y Z: 256 (GFLOP/s)",HIB,38.9613,38.6757 "libxsmm - M N K: 64 (GFLOPS/s)",HIB,833.8,839.9 "srsRAN Project - Test: Downlink Processor Benchmark (Mbps)",HIB,705.8,710.9 "Apache IoTDB - Device Count: 100 - Batch Size Per Write: 1 - Sensor Count: 500 (Latency)",HIB,28.27,28.45 "Stress-NG - Test: MMAP (Bogo Ops/s)",HIB,861.28,856.14 "HeFFTe - Highly Efficient FFT for Exascale - Test: r2c - Backend: FFTW - Precision: double - X Y Z: 128 (GFLOP/s)",HIB,121.794,122.460 "Palabos - Grid Size: 400 (Mega Site Updates/sec)",HIB,287.268,285.761 "Apache IoTDB - Device Count: 100 - Batch Size Per Write: 1 - Sensor Count: 500 (point/sec)",HIB,1191500.88,1185338.02 "HeFFTe - Highly Efficient FFT for Exascale - Test: c2c - Backend: FFTW - Precision: float - X Y Z: 128 (GFLOP/s)",HIB,131.656,130.982 "HeFFTe - Highly Efficient FFT for Exascale - Test: r2c - Backend: FFTW - Precision: float - X Y Z: 128 (GFLOP/s)",HIB,207.244,206.217 "Laghos - Test: Triple Point Problem (Major Kernels Rate)",HIB,177.78,176.92 "Apache IoTDB - Device Count: 500 - Batch Size Per Write: 100 - Sensor Count: 500 (Latency)",HIB,68.34,68.01 "Neural Magic DeepSparse - Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,345.1491,343.5170 "Neural Magic DeepSparse - Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,46.3307,46.5491 "Stress-NG - Test: Fused Multiply-Add (Bogo Ops/s)",HIB,34197705.63,34050669.23 "High Performance Conjugate Gradient - X Y Z: 160 160 160 - RT: 60 (GFLOP/s)",HIB,27.5086,27.3978 "Stress-NG - Test: Function Call (Bogo Ops/s)",HIB,22028.03,22106.49 "Apache IoTDB - Device Count: 500 - Batch Size Per Write: 100 - Sensor Count: 200 (Latency)",HIB,31.58,31.69 "HeFFTe - Highly Efficient FFT for Exascale - Test: r2c - Backend: FFTW - Precision: double - X Y Z: 512 (GFLOP/s)",HIB,74.4734,74.7148 "Liquid-DSP - Threads: 32 - Buffer Length: 256 - Filter Length: 57 (samples/s)",HIB,1328100000,1323900000 "Stress-NG - Test: NUMA (Bogo Ops/s)",HIB,390.87,392.08 "Stress-NG - Test: Mutex (Bogo Ops/s)",HIB,15147444.51,15192892.59 "HeFFTe - Highly Efficient FFT for Exascale - Test: c2c - Backend: Stock - Precision: float - X Y Z: 128 (GFLOP/s)",HIB,85.7398,85.4850 "Neural Magic DeepSparse - Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,131.4497,131.0664 "Neural Magic DeepSparse - Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,121.6893,122.0367 "Stress-NG - Test: Wide Vector Math (Bogo Ops/s)",HIB,1745029.27,1750003.43 "Apache IoTDB - Device Count: 200 - Batch Size Per Write: 1 - Sensor Count: 200 (point/sec)",HIB,1045806.81,1042859.03 "Liquid-DSP - Threads: 64 - Buffer Length: 256 - Filter Length: 57 (samples/s)",HIB,1728850000,1733700000 "Neural Magic DeepSparse - Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,390.9076,391.9125 "Neural Magic DeepSparse - Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,40.9109,40.8061 "VVenC - Video Input: Bosphorus 4K - Video Preset: Faster (FPS)",HIB,11.020,10.992 "Redis 7.0.12 + memtier_benchmark - Protocol: Redis - Clients: 50 - Set To Get Ratio: 1:5 (Ops/sec)",HIB,2211638.65,2217192.12 "Timed GDB GNU Debugger Compilation - Time To Compile (sec)",LIB,41.905,42.006 "Stress-NG - Test: Glibc C String Functions (Bogo Ops/s)",HIB,26067360.60,26125214.84 "High Performance Conjugate Gradient - X Y Z: 104 104 104 - RT: 60 (GFLOP/s)",HIB,27.7808,27.8405 "HeFFTe - Highly Efficient FFT for Exascale - Test: c2c - Backend: Stock - Precision: float - X Y Z: 256 (GFLOP/s)",HIB,75.0892,74.9286 "OpenFOAM - Input: drivaerFastback, Small Mesh Size - Execution Time (sec)",LIB,67.707331,67.563163 "Neural Magic DeepSparse - Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,3227.0954,3233.9588 "Neural Magic DeepSparse - Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,4.9416,4.9312 "HeFFTe - Highly Efficient FFT for Exascale - Test: c2c - Backend: Stock - Precision: double - X Y Z: 512 (GFLOP/s)",HIB,40.7438,40.6648 "Palabos - Grid Size: 500 (Mega Site Updates/sec)",HIB,300.276,300.855 "HeFFTe - Highly Efficient FFT for Exascale - Test: r2c - Backend: Stock - Precision: double - X Y Z: 256 (GFLOP/s)",HIB,76.9042,77.0345 "HeFFTe - Highly Efficient FFT for Exascale - Test: c2c - Backend: FFTW - Precision: float - X Y Z: 512 (GFLOP/s)",HIB,78.8291,78.9605 "OpenFOAM - Input: drivaerFastback, Medium Mesh Size - Mesh Time (sec)",LIB,144.69646,144.93674 "HeFFTe - Highly Efficient FFT for Exascale - Test: r2c - Backend: FFTW - Precision: float - X Y Z: 512 (GFLOP/s)",HIB,141.41,141.193 "Neural Magic DeepSparse - Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,479.7876,480.5223 "Laghos - Test: Sedov Blast Wave, ube_922_hex.mesh (Major Kernels Rate)",HIB,216.86,217.19 "Neural Magic DeepSparse - Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,33.3278,33.2781 "Blender - Blend File: BMW27 - Compute: CPU-Only (sec)",LIB,47.15,47.22 "HeFFTe - Highly Efficient FFT for Exascale - Test: r2c - Backend: Stock - Precision: float - X Y Z: 512 (GFLOP/s)",HIB,137.536,137.740 "Stress-NG - Test: AVL Tree (Bogo Ops/s)",HIB,294.26,294.66 "Palabos - Grid Size: 100 (Mega Site Updates/sec)",HIB,235.186,234.874 "Stress-NG - Test: Floating Point (Bogo Ops/s)",HIB,10587.48,10601.10 "Liquid-DSP - Threads: 16 - Buffer Length: 256 - Filter Length: 32 (samples/s)",HIB,557945000,558655000 "HeFFTe - Highly Efficient FFT for Exascale - Test: r2c - Backend: FFTW - Precision: double - X Y Z: 256 (GFLOP/s)",HIB,72.2893,72.1981 "Stress-NG - Test: Malloc (Bogo Ops/s)",HIB,99373474.31,99251227.28 "Stress-NG - Test: Hash (Bogo Ops/s)",HIB,5577252.32,5583978.14 "Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,76.5597,76.4684 "High Performance Conjugate Gradient - X Y Z: 144 144 144 - RT: 60 (GFLOP/s)",HIB,27.4213,27.3890 "Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,1074.8218,1075.9571 "Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,504.6114,505.1309 "Timed LLVM Compilation - Build System: Ninja (sec)",LIB,263.154,262.884 "Stress-NG - Test: Pthread (Bogo Ops/s)",HIB,136846.01,136709.81 "Blender - Blend File: Fishy Cat - Compute: CPU-Only (sec)",LIB,64.07,64.01 "HeFFTe - Highly Efficient FFT for Exascale - Test: c2c - Backend: FFTW - Precision: double - X Y Z: 512 (GFLOP/s)",HIB,43.9665,44.0064 "OpenFOAM - Input: drivaerFastback, Medium Mesh Size - Execution Time (sec)",LIB,615.99074,615.46018 "Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,14.8600,14.8473 "Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,31.6750,31.6488 "Timed PHP Compilation - Time To Compile (sec)",LIB,42.351,42.382 "Stress-NG - Test: MEMFD (Bogo Ops/s)",HIB,549.94,549.55 "Liquid-DSP - Threads: 32 - Buffer Length: 256 - Filter Length: 32 (samples/s)",HIB,847085000,847675000 "Stress-NG - Test: Context Switching (Bogo Ops/s)",HIB,2572801.75,2571092.69 "Neural Magic DeepSparse - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,34.5311,34.5539 "Neural Magic DeepSparse - Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,478.9108,479.2241 "Neural Magic DeepSparse - Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,33.3894,33.3680 "Stress-NG - Test: Poll (Bogo Ops/s)",HIB,3669281.69,3671617.97 "VVenC - Video Input: Bosphorus 1080p - Video Preset: Faster (FPS)",HIB,30.946,30.927 "Stress-NG - Test: Memory Copying (Bogo Ops/s)",HIB,7176.19,7180.43 "OpenFOAM - Input: drivaerFastback, Small Mesh Size - Mesh Time (sec)",LIB,27.965214,27.948717 "Stress-NG - Test: Matrix 3D Math (Bogo Ops/s)",HIB,9599.93,9605.30 "Stress-NG - Test: Forking (Bogo Ops/s)",HIB,89918.21,89966.29 "Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,208.8975,208.9908 "Stress-NG - Test: Glibc Qsort Data Sorting (Bogo Ops/s)",HIB,696.65,696.92 "Stress-NG - Test: Zlib (Bogo Ops/s)",HIB,2647.81,2648.81 "Stress-NG - Test: System V Message Passing (Bogo Ops/s)",HIB,5852281.71,5854201.78 "Blender - Blend File: Barbershop - Compute: CPU-Only (sec)",LIB,493.45,493.61 "Timed Linux Kernel Compilation - Build: defconfig (sec)",LIB,40.438,40.451 "HeFFTe - Highly Efficient FFT for Exascale - Test: c2c - Backend: Stock - Precision: float - X Y Z: 512 (GFLOP/s)",HIB,72.5609,72.5391 "Stress-NG - Test: Vector Math (Bogo Ops/s)",HIB,151386.31,151431.15 "Liquid-DSP - Threads: 64 - Buffer Length: 256 - Filter Length: 32 (samples/s)",HIB,1577300000,1576850000 "Liquid-DSP - Threads: 64 - Buffer Length: 256 - Filter Length: 512 (samples/s)",HIB,513135000,513040000 "Stress-NG - Test: Vector Floating Point (Bogo Ops/s)",HIB,58243.38,58232.70 "Blender - Blend File: Classroom - Compute: CPU-Only (sec)",LIB,127.78,127.76 "Stress-NG - Test: CPU Stress (Bogo Ops/s)",HIB,64111.11,64118.87 "HeFFTe - Highly Efficient FFT for Exascale - Test: r2c - Backend: Stock - Precision: double - X Y Z: 512 (GFLOP/s)",HIB,76.6110,76.6041 "Stress-NG - Test: Crypto (Bogo Ops/s)",HIB,50240.09,50243.48 "Neural Magic DeepSparse - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,460.7818,460.7588 "Stress-NG - Test: x86_64 RdRand (Bogo Ops/s)",HIB,331416.52,331423.04 "Stress-NG - Test: Vector Shuffle (Bogo Ops/s)",HIB,167204.21,167202.07 "Timed Linux Kernel Compilation - Build: allmodconfig (sec)",LIB,445.385,445.380 "BRL-CAD - VGR Performance Metric (VGR Performance Metric)",HIB,466686, "Apache Cassandra - Test: Writes (Op/s)",HIB,155626, "Blender - Blend File: Pabellon Barcelona - Compute: CPU-Only (sec)",LIB,159.94, "Redis 7.0.12 + memtier_benchmark - Protocol: Redis - Clients: 500 - Set To Get Ratio: 1:10 ()",,, "Redis 7.0.12 + memtier_benchmark - Protocol: Redis - Clients: 500 - Set To Get Ratio: 1:5 ()",,,