AMD Ryzen 9 3900XT 12-Core testing with a MSI MEG X570 GODLIKE (MS-7C34) v1.0 (1.B3 BIOS) and AMD Radeon RX 56/64 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 2211180-SYST-3900XTN38
3900xt-november
AMD Ryzen 9 3900XT 12-Core testing with a MSI MEG X570 GODLIKE (MS-7C34) v1.0 (1.B3 BIOS) and AMD Radeon RX 56/64 8GB on Ubuntu 22.04 via the Phoronix Test Suite.
,,"a","aa","b"
Processor,,AMD Ryzen 9 3900XT 12-Core @ 3.80GHz (12 Cores / 24 Threads),AMD Ryzen 9 3900XT 12-Core @ 3.80GHz (12 Cores / 24 Threads),AMD Ryzen 9 3900XT 12-Core @ 3.80GHz (12 Cores / 24 Threads)
Motherboard,,MSI MEG X570 GODLIKE (MS-7C34) v1.0 (1.B3 BIOS),MSI MEG X570 GODLIKE (MS-7C34) v1.0 (1.B3 BIOS),MSI MEG X570 GODLIKE (MS-7C34) v1.0 (1.B3 BIOS)
Chipset,,AMD Starship/Matisse,AMD Starship/Matisse,AMD Starship/Matisse
Memory,,16GB,16GB,16GB
Disk,,500GB Seagate FireCuda 520 SSD ZP500GM30002,500GB Seagate FireCuda 520 SSD ZP500GM30002,500GB Seagate FireCuda 520 SSD ZP500GM30002
Graphics,,AMD Radeon RX 56/64 8GB (1630/945MHz),AMD Radeon RX 56/64 8GB (1630/945MHz),AMD Radeon RX 56/64 8GB (1630/945MHz)
Audio,,AMD Vega 10 HDMI Audio,AMD Vega 10 HDMI Audio,AMD Vega 10 HDMI Audio
Monitor,,ASUS MG28U,ASUS MG28U,ASUS MG28U
Network,,Realtek Device 2600 + Realtek Killer E3000 2.5GbE + Intel Wi-Fi 6 AX200,Realtek Device 2600 + Realtek Killer E3000 2.5GbE + Intel Wi-Fi 6 AX200,Realtek Device 2600 + Realtek Killer E3000 2.5GbE + Intel Wi-Fi 6 AX200
OS,,Ubuntu 22.04,Ubuntu 22.04,Ubuntu 22.04
Kernel,,5.15.0-47-generic (x86_64),5.15.0-47-generic (x86_64),5.15.0-47-generic (x86_64)
Desktop,,GNOME Shell 42.2,GNOME Shell 42.2,GNOME Shell 42.2
Display Server,,X Server + Wayland,X Server + Wayland,X Server + Wayland
OpenGL,,4.6 Mesa 22.0.1 (LLVM 13.0.1 DRM 3.42),4.6 Mesa 22.0.1 (LLVM 13.0.1 DRM 3.42),4.6 Mesa 22.0.1 (LLVM 13.0.1 DRM 3.42)
Vulkan,,1.3.204,1.3.204,1.3.204
Compiler,,GCC 11.2.0,GCC 11.2.0,GCC 11.2.0
File-System,,ext4,ext4,ext4
Screen Resolution,,3840x2160,3840x2160,3840x2160
,,"a","aa","b"
"miniBUDE - Implementation: OpenMP - Input Deck: BM1 (Billion Interactions/s)",HIB,16.233,16.268,16.170
"miniBUDE - Implementation: OpenMP - Input Deck: BM2 (Billion Interactions/s)",HIB,16.394,16.412,16.405
"Stress-NG - Test: MMAP (Bogo Ops/s)",HIB,294.05,292.1,293.29
"Stress-NG - Test: NUMA (Bogo Ops/s)",HIB,260.68,261.26,260.02
"Stress-NG - Test: Futex (Bogo Ops/s)",HIB,2600010.05,2717409.38,2563831.67
"Stress-NG - Test: MEMFD (Bogo Ops/s)",HIB,747.31,773.07,770.89
"Stress-NG - Test: Mutex (Bogo Ops/s)",HIB,6319425.86,6371966.37,6344621.56
"Stress-NG - Test: Atomic (Bogo Ops/s)",HIB,575564.96,575708.53,571674.68
"Stress-NG - Test: Crypto (Bogo Ops/s)",HIB,22523.79,22525.14,22434.69
"Stress-NG - Test: Malloc (Bogo Ops/s)",HIB,13779284.62,13924963.43,13767394.33
"Stress-NG - Test: Forking (Bogo Ops/s)",HIB,40818.92,40572.79,40197.6
"Stress-NG - Test: IO_uring (Bogo Ops/s)",HIB,5126.99,8765.88,4168.54
"Stress-NG - Test: SENDFILE (Bogo Ops/s)",HIB,215308.14,215163.99,205666.12
"Stress-NG - Test: CPU Cache (Bogo Ops/s)",HIB,158.89,152.46,149.79
"Stress-NG - Test: CPU Stress (Bogo Ops/s)",HIB,32900.39,31954.78,30793.53
"Stress-NG - Test: Semaphores (Bogo Ops/s)",HIB,2463565.68,2465656.19,2466594.73
"Stress-NG - Test: Matrix Math (Bogo Ops/s)",HIB,61078.06,61203.21,58814.38
"Stress-NG - Test: Vector Math (Bogo Ops/s)",HIB,90999.65,90998.92,87587.66
"Stress-NG - Test: Memory Copying (Bogo Ops/s)",HIB,3599.42,3592.78,3456.53
"Stress-NG - Test: Socket Activity (Bogo Ops/s)",HIB,8595.2,8500.17,8961.2
"Stress-NG - Test: Context Switching (Bogo Ops/s)",HIB,4076744.52,4103283.77,3796353.99
"Stress-NG - Test: Glibc C String Functions (Bogo Ops/s)",HIB,2048965.25,2035501.44,1531955.88
"Stress-NG - Test: Glibc Qsort Data Sorting (Bogo Ops/s)",HIB,180.77,192.23,184.77
"Stress-NG - Test: System V Message Passing (Bogo Ops/s)",HIB,7925418.15,7932169.44,7654922.05
"nekRS - Input: TurboPipe Periodic (FLOP/s)",HIB,31559900000,32575200000,32544333333
"Libplacebo - Test: deband_heavy (FPS)",HIB,476.59,479.65,474.53
"Libplacebo - Test: polar_nocompute (FPS)",HIB,977.72,948.28,961.48
"Libplacebo - Test: hdr_peakdetect (FPS)",HIB,2610.2,2598.97,2603.19
"Libplacebo - Test: hdr_lut (FPS)",HIB,2797.23,2806.16,2840.16
"Libplacebo - Test: av1_grain_lap (FPS)",HIB,2073.69,2106.73,2093.70
"QuadRay - Scene: 1 - Resolution: 4K (FPS)",HIB,10.21,9.63,10.14
"QuadRay - Scene: 2 - Resolution: 4K (FPS)",HIB,2.89,2.9,2.86
"QuadRay - Scene: 3 - Resolution: 4K (FPS)",HIB,2.46,2.43,2.49
"QuadRay - Scene: 5 - Resolution: 4K (FPS)",HIB,0.66,0.66,0.66
"QuadRay - Scene: 1 - Resolution: 1080p (FPS)",HIB,39.48,38.5,39.26
"QuadRay - Scene: 2 - Resolution: 1080p (FPS)",HIB,11.12,11.22,11.17
"QuadRay - Scene: 3 - Resolution: 1080p (FPS)",HIB,9.71,9.81,9.70
"QuadRay - Scene: 5 - Resolution: 1080p (FPS)",HIB,2.64,2.62,2.63
"FFmpeg - Encoder: libx264 - Scenario: Live (FPS)",HIB,204.75,205.03,204.73
"FFmpeg - Encoder: libx265 - Scenario: Live (FPS)",HIB,75.38,75.50,75.10
"FFmpeg - Encoder: libx264 - Scenario: Upload (FPS)",HIB,12.64,12.64,12.67
"FFmpeg - Encoder: libx265 - Scenario: Upload (FPS)",HIB,15.32,15.33,15.37
"FFmpeg - Encoder: libx264 - Scenario: Platform (FPS)",HIB,48.84,49.01,48.62
"FFmpeg - Encoder: libx265 - Scenario: Platform (FPS)",HIB,31.31,31.49,31.55
"FFmpeg - Encoder: libx264 - Scenario: Video On Demand (FPS)",HIB,48.83,48.85,48.77
"FFmpeg - Encoder: libx265 - Scenario: Video On Demand (FPS)",HIB,31.45,31.62,31.56
"AOM AV1 - Encoder Mode: Speed 0 Two-Pass - Input: Bosphorus 4K (FPS)",HIB,0.25,0.25,0.25
"AOM AV1 - Encoder Mode: Speed 4 Two-Pass - Input: Bosphorus 4K (FPS)",HIB,7.41,7.45,7.41
"AOM AV1 - Encoder Mode: Speed 6 Realtime - Input: Bosphorus 4K (FPS)",HIB,23.1,23.2,23.13
"AOM AV1 - Encoder Mode: Speed 6 Two-Pass - Input: Bosphorus 4K (FPS)",HIB,12.67,12.68,12.71
"AOM AV1 - Encoder Mode: Speed 8 Realtime - Input: Bosphorus 4K (FPS)",HIB,34.46,34.91,34.60
"AOM AV1 - Encoder Mode: Speed 9 Realtime - Input: Bosphorus 4K (FPS)",HIB,47.42,47.62,47.60
"AOM AV1 - Encoder Mode: Speed 10 Realtime - Input: Bosphorus 4K (FPS)",HIB,47.55,47.95,48.23
"AOM AV1 - Encoder Mode: Speed 0 Two-Pass - Input: Bosphorus 1080p (FPS)",HIB,0.73,0.73,0.73
"AOM AV1 - Encoder Mode: Speed 4 Two-Pass - Input: Bosphorus 1080p (FPS)",HIB,15.08,15.01,15.12
"AOM AV1 - Encoder Mode: Speed 6 Realtime - Input: Bosphorus 1080p (FPS)",HIB,45.2,46.98,45.64
"AOM AV1 - Encoder Mode: Speed 6 Two-Pass - Input: Bosphorus 1080p (FPS)",HIB,41.57,42.17,42.07
"AOM AV1 - Encoder Mode: Speed 8 Realtime - Input: Bosphorus 1080p (FPS)",HIB,85.22,85.9,84.93
"AOM AV1 - Encoder Mode: Speed 9 Realtime - Input: Bosphorus 1080p (FPS)",HIB,108.47,108.91,107.41
"AOM AV1 - Encoder Mode: Speed 10 Realtime - Input: Bosphorus 1080p (FPS)",HIB,109.52,111.49,110.26
"miniBUDE - Implementation: OpenMP - Input Deck: BM1 (GFInst/s)",HIB,405.816,406.706,404.247
"miniBUDE - Implementation: OpenMP - Input Deck: BM2 (GFInst/s)",HIB,409.855,410.307,410.141
"Xmrig - Variant: Monero - Hash Count: 1M (H/s)",HIB,7982.6,7945.8,8175.8
"Xmrig - Variant: Wownero - Hash Count: 1M (H/s)",HIB,10466.6,10640,10577.3
"TensorFlow - Device: CPU - Batch Size: 16 - Model: AlexNet (images/sec)",HIB,55.63,55.47,55.49
"TensorFlow - Device: CPU - Batch Size: 32 - Model: AlexNet (images/sec)",HIB,76.22,76.25,76.37
"TensorFlow - Device: CPU - Batch Size: 64 - Model: AlexNet (images/sec)",HIB,93.8,93.88,93.79
"TensorFlow - Device: CPU - Batch Size: 256 - Model: AlexNet (images/sec)",HIB,109.23,109.38,109.30
"TensorFlow - Device: CPU - Batch Size: 512 - Model: AlexNet (images/sec)",HIB,110.36,110.49,110.02
"TensorFlow - Device: CPU - Batch Size: 16 - Model: GoogLeNet (images/sec)",HIB,31.89,31.83,31.85
"TensorFlow - Device: CPU - Batch Size: 16 - Model: ResNet-50 (images/sec)",HIB,10.39,10.44,10.44
"TensorFlow - Device: CPU - Batch Size: 32 - Model: GoogLeNet (images/sec)",HIB,30.46,30.58,30.48
"TensorFlow - Device: CPU - Batch Size: 32 - Model: ResNet-50 (images/sec)",HIB,10.29,10.29,10.33
"TensorFlow - Device: CPU - Batch Size: 64 - Model: GoogLeNet (images/sec)",HIB,30.55,30.51,30.50
"TensorFlow - Device: CPU - Batch Size: 64 - Model: ResNet-50 (images/sec)",HIB,10.09,10.06,10.12
"TensorFlow - Device: CPU - Batch Size: 256 - Model: GoogLeNet (images/sec)",HIB,28.64,28.67,28.65
"TensorFlow - Device: CPU - Batch Size: 512 - Model: GoogLeNet (images/sec)",HIB,28.79,28.71,28.33
"Neural Magic DeepSparse - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,9.7748,9.7085,9.6761
"Neural Magic DeepSparse - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Stream (items/sec)",HIB,7.9776,7.989,7.9824
"Neural Magic DeepSparse - Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,33.2144,33.0595,32.914
"Neural Magic DeepSparse - Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Synchronous Single-Stream (items/sec)",HIB,20.6208,20.3104,20.2026
"Neural Magic DeepSparse - Model: CV Detection,YOLOv5s COCO - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,52.8476,52.7812,52.4162
"Neural Magic DeepSparse - Model: CV Detection,YOLOv5s COCO - Scenario: Synchronous Single-Stream (items/sec)",HIB,42.4309,42.4149,42.3627
"Neural Magic DeepSparse - Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,112.2815,112.2567,112.1223
"Neural Magic DeepSparse - Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Stream (items/sec)",HIB,78.3889,78.4088,78.3062
"Neural Magic DeepSparse - Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,81.374,81.044,81.3092
"Neural Magic DeepSparse - Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Stream (items/sec)",HIB,59.4485,59.619,59.4138
"Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,40.9537,41.0572,40.9084
"Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Synchronous Single-Stream (items/sec)",HIB,29.9481,30.0041,29.9886
"Neural Magic DeepSparse - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,9.7133,9.723,9.8238
"Neural Magic DeepSparse - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Stream (items/sec)",HIB,8.0129,8.0151,7.9966
"Cpuminer-Opt - Algorithm: Magi (kH/s)",HIB,603.58,603.33,600.87
"Cpuminer-Opt - Algorithm: x25x (kH/s)",HIB,631.15,631.74,628.47
"Cpuminer-Opt - Algorithm: scrypt (kH/s)",HIB,226.42,226.59,225.89
"Cpuminer-Opt - Algorithm: Deepcoin (kH/s)",HIB,11710,11720,11660
"Cpuminer-Opt - Algorithm: Ringcoin (kH/s)",HIB,2705.27,2709.03,2730.30
"Cpuminer-Opt - Algorithm: Blake-2 S (kH/s)",HIB,524680,528060,519433
"Cpuminer-Opt - Algorithm: Garlicoin (kH/s)",HIB,1939.65,1960.71,2112.41
"Cpuminer-Opt - Algorithm: Skeincoin (kH/s)",HIB,106880,108620,105667
"Cpuminer-Opt - Algorithm: Myriad-Groestl (kH/s)",HIB,21130,21260,21397
"Cpuminer-Opt - Algorithm: LBC, LBRY Credits (kH/s)",HIB,31260,31820,31143
"Cpuminer-Opt - Algorithm: Quad SHA-256, Pyrite (kH/s)",HIB,102170,102180,102017
"Cpuminer-Opt - Algorithm: Triple SHA-256, Onecoin (kH/s)",HIB,204970,204950,205100
"SMHasher - Hash: wyhash (MiB/sec)",HIB,23915.75,24070.66,23571.26
"SMHasher - Hash: SHA3-256 (MiB/sec)",HIB,149.08,148.14,151.76
"SMHasher - Hash: Spooky32 (MiB/sec)",HIB,14909.02,15026.6,14856.10
"SMHasher - Hash: fasthash32 (MiB/sec)",HIB,6658.92,6917.32,6686.25
"SMHasher - Hash: FarmHash128 (MiB/sec)",HIB,15884.24,16614.28,16361.64
"SMHasher - Hash: t1ha2_atonce (MiB/sec)",HIB,16686.57,15706.92,16085.48
"SMHasher - Hash: FarmHash32 x86_64 AVX (MiB/sec)",HIB,29093.03,28582.22,27788.51
"SMHasher - Hash: t1ha0_aes_avx2 x86_64 (MiB/sec)",HIB,66796.46,69896.41,68310.66
"SMHasher - Hash: MeowHash x86_64 AES-NI (MiB/sec)",HIB,37183.28,37904.32,38610.17
"JPEG XL libjxl - Input: PNG - Quality: 80 (MP/s)",HIB,9.08,9.13,9.12
"JPEG XL libjxl - Input: PNG - Quality: 90 (MP/s)",HIB,9.02,9.03,9.07
"JPEG XL libjxl - Input: JPEG - Quality: 80 (MP/s)",HIB,8.68,8.98,8.84
"JPEG XL libjxl - Input: JPEG - Quality: 90 (MP/s)",HIB,8.62,8.76,8.80
"JPEG XL libjxl - Input: PNG - Quality: 100 (MP/s)",HIB,0.69,0.69,0.69
"JPEG XL libjxl - Input: JPEG - Quality: 100 (MP/s)",HIB,0.68,0.68,0.68
"JPEG XL Decoding libjxl - CPU Threads: 1 (MP/s)",HIB,48.69,47.21,48.24
"JPEG XL Decoding libjxl - CPU Threads: All (MP/s)",HIB,146.63,148.61,148.59
"nginx - Connections: 100 (Reqs/sec)",HIB,87222.68,86726.1,83591.65
"nginx - Connections: 200 (Reqs/sec)",HIB,83513.14,84210.42,82789.42
"nginx - Connections: 500 (Reqs/sec)",HIB,75259.81,76617.7,76562.05
"nginx - Connections: 1000 (Reqs/sec)",HIB,65135.63,65507.92,66302.86
"spaCy - Model: en_core_web_lg (tokens/sec)",HIB,12196,12217,11978
"spaCy - Model: en_core_web_trf (tokens/sec)",HIB,832,833,550
"SMHasher - Hash: wyhash (cycles/hash)",LIB,25.309,25.29,25.914
"SMHasher - Hash: SHA3-256 (cycles/hash)",LIB,2598.05,2620.221,2564.206
"SMHasher - Hash: Spooky32 (cycles/hash)",LIB,49.056,48.98,49.500
"SMHasher - Hash: fasthash32 (cycles/hash)",LIB,36.902,35.257,36.688
"SMHasher - Hash: FarmHash128 (cycles/hash)",LIB,64.103,60.336,61.812
"SMHasher - Hash: t1ha2_atonce (cycles/hash)",LIB,32.254,34.548,33.679
"SMHasher - Hash: FarmHash32 x86_64 AVX (cycles/hash)",LIB,40.069,41.134,42.575
"SMHasher - Hash: t1ha0_aes_avx2 x86_64 (cycles/hash)",LIB,34.811,32.875,33.612
"SMHasher - Hash: MeowHash x86_64 AES-NI (cycles/hash)",LIB,57.74,56.976,55.875
"oneDNN - Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU (ms)",LIB,4.69026,4.74859,4.73086
"oneDNN - Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU (ms)",LIB,12.0602,12.0288,12.0313
"oneDNN - Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU (ms)",LIB,22.5449,22.5504,22.5210
"oneDNN - Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU (ms)",LIB,8.2274,5.47125,6.22396
"oneDNN - Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU (ms)",LIB,5.27435,5.25072,5.28794
"oneDNN - Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU (ms)",LIB,4075.57,4145.83,4147.65
"oneDNN - Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU (ms)",LIB,2503.12,2484.9,2481.61
"oneDNN - Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU (ms)",LIB,1.8817,1.27895,1.74121
"Neural Magic DeepSparse - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,611.8404,617.7405,618.1363
"Neural Magic DeepSparse - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Stream (ms/batch)",LIB,125.3455,125.1653,125.2691
"Neural Magic DeepSparse - Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,180.6052,181.4556,182.2569
"Neural Magic DeepSparse - Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Synchronous Single-Stream (ms/batch)",LIB,48.4869,49.228,49.4908
"Neural Magic DeepSparse - Model: CV Detection,YOLOv5s COCO - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,113.4603,113.6428,114.4037
"Neural Magic DeepSparse - Model: CV Detection,YOLOv5s COCO - Scenario: Synchronous Single-Stream (ms/batch)",LIB,23.5574,23.5672,23.596
"Neural Magic DeepSparse - Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,53.4102,53.4052,53.4398
"Neural Magic DeepSparse - Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Stream (ms/batch)",LIB,12.7499,12.7463,12.7634
"Neural Magic DeepSparse - Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,73.7085,74.0117,73.7666
"Neural Magic DeepSparse - Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Stream (ms/batch)",LIB,16.8159,16.7678,16.8258
"Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,146.4793,146.1108,146.6414
"Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Synchronous Single-Stream (ms/batch)",LIB,33.3853,33.3228,33.3404
"Neural Magic DeepSparse - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,617.6457,617.0345,609.8345
"Neural Magic DeepSparse - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Stream (ms/batch)",LIB,124.7919,124.7582,125.0469
"OpenFOAM - Input: drivaerFastback, Small Mesh Size - Mesh Time (sec)",LIB,41.823568,41.852307,42.077007
"OpenFOAM - Input: drivaerFastback, Small Mesh Size - Execution Time (sec)",LIB,363.21657,361.47957,359.99903
"OpenRadioss - Model: Bumper Beam (sec)",LIB,127.42,126.51,127.37
"OpenRadioss - Model: Cell Phone Drop Test (sec)",LIB,104.51,104.11,104.27
"OpenRadioss - Model: Bird Strike on Windshield (sec)",LIB,285.69,286.84,287.33
"OpenRadioss - Model: Rubber O-Ring Seal Installation (sec)",LIB,131,130.82,130.06
"OpenRadioss - Model: INIVOL and Fluid Structure Interaction Drop Container (sec)",LIB,633.97,650.25,631.33
"libavif avifenc - Encoder Speed: 0 (sec)",LIB,130.357,131.57,130.149
"libavif avifenc - Encoder Speed: 2 (sec)",LIB,63.121,64.019,64.373
"libavif avifenc - Encoder Speed: 6 (sec)",LIB,6.049,6.076,6.019
"libavif avifenc - Encoder Speed: 6, Lossless (sec)",LIB,10.149,10.094,10.152
"libavif avifenc - Encoder Speed: 10, Lossless (sec)",LIB,5.48,5.505,5.497
"Y-Cruncher - Pi Digits To Calculate: 1B (sec)",LIB,41.524,41.841,41.426
"Y-Cruncher - Pi Digits To Calculate: 500M (sec)",LIB,19.547,19.527,19.531
"FLAC Audio Encoding - WAV To FLAC (sec)",LIB,17.255,17.326,17.209
"FFmpeg - Encoder: libx264 - Scenario: Live (sec)",LIB,24.66,24.63,24.67
"FFmpeg - Encoder: libx265 - Scenario: Live (sec)",LIB,66.99,66.89,67.26
"FFmpeg - Encoder: libx264 - Scenario: Upload (sec)",LIB,199.730241377,199.81,199.35
"FFmpeg - Encoder: libx265 - Scenario: Upload (sec)",LIB,164.797431657,164.72,164.26
"FFmpeg - Encoder: libx264 - Scenario: Platform (sec)",LIB,155.11,154.57,155.81
"FFmpeg - Encoder: libx265 - Scenario: Platform (sec)",LIB,241.928872179,240.520175955,240.09
"FFmpeg - Encoder: libx264 - Scenario: Video On Demand (sec)",LIB,155.137732285,155.058138517,155.31
"FFmpeg - Encoder: libx265 - Scenario: Video On Demand (sec)",LIB,240.839641179,239.59,240.03
"EnCodec - Target Bandwidth: 3 kbps (sec)",LIB,47.231,47.659,48.45
"EnCodec - Target Bandwidth: 6 kbps (sec)",LIB,47.326,48.564,48.215
"EnCodec - Target Bandwidth: 24 kbps (sec)",LIB,54.416,54.426,54.862
"EnCodec - Target Bandwidth: 1.5 kbps (sec)",LIB,45.14,46.082,46.624