Intel Core i7-8565U testing with a Dell 0KTW76 (1.17.0 BIOS) and Intel UHD 620 WHL GT2 15GB 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 2308067-NE-DDDXXX42317
dddxxx
Intel Core i7-8565U testing with a Dell 0KTW76 (1.17.0 BIOS) and Intel UHD 620 WHL GT2 15GB on Ubuntu 22.04 via the Phoronix Test Suite.
,,"a","b"
Processor,,Intel Core i7-8565U @ 4.60GHz (4 Cores / 8 Threads),Intel Core i7-8565U @ 4.60GHz (4 Cores / 8 Threads)
Motherboard,,Dell 0KTW76 (1.17.0 BIOS),Dell 0KTW76 (1.17.0 BIOS)
Chipset,,Intel Cannon Point-LP,Intel Cannon Point-LP
Memory,,16GB,16GB
Disk,,SK hynix PC401 NVMe 256GB,SK hynix PC401 NVMe 256GB
Graphics,,Intel UHD 620 WHL GT2 15GB (1150MHz),Intel UHD 620 WHL GT2 15GB (1150MHz)
Audio,,Realtek ALC3271,Realtek ALC3271
Network,,Qualcomm Atheros QCA6174 802.11ac,Qualcomm Atheros QCA6174 802.11ac
OS,,Ubuntu 22.04,Ubuntu 22.04
Kernel,,5.19.0-rc6-phx-retbleed (x86_64),5.19.0-rc6-phx-retbleed (x86_64)
Desktop,,GNOME Shell 42.2,GNOME Shell 42.2
Display Server,,X Server + Wayland,X Server + Wayland
OpenGL,,4.6 Mesa 22.0.1,4.6 Mesa 22.0.1
OpenCL,,OpenCL 3.0,OpenCL 3.0
Vulkan,,1.3.204,1.3.204
Compiler,,GCC 11.3.0,GCC 11.4.0
File-System,,ext4,ext4
Screen Resolution,,1920x1080,1920x1080
,,"a","b"
"Timed LLVM Compilation - Build System: Unix Makefiles (sec)",LIB,2967.528,2929.911
"Timed LLVM Compilation - Build System: Ninja (sec)",LIB,2892.088,2908.878
"Timed Godot Game Engine Compilation - Time To Compile (sec)",LIB,1372.604,1384.766
"Apache IoTDB - Device Count: 500 - Batch Size Per Write: 100 - Sensor Count: 500 (Latency)",HIB,984.7,1026.93
"Apache IoTDB - Device Count: 500 - Batch Size Per Write: 100 - Sensor Count: 500 (point/sec)",HIB,4948660.19,4629287.79
"Xonotic - Resolution: 1920 x 1080 - Effects Quality: Ultimate (FPS)",HIB,59.1708882,58.9499391
"Build2 - Time To Compile (sec)",LIB,555.936,569.609
"VVenC - Video Input: Bosphorus 4K - Video Preset: Fast (FPS)",HIB,1.180,1.170
"Xonotic - Resolution: 1920 x 1080 - Effects Quality: Ultra (FPS)",HIB,77.9338736,77.5195887
"Xonotic - Resolution: 1920 x 1080 - Effects Quality: High (FPS)",HIB,91.1145989,90.9080095
"Intel Open Image Denoise - Run: RTLightmap.hdr.4096x4096 - Device: CPU-Only (Images / Sec)",HIB,0.06,0.06
"libxsmm - M N K: 128 (GFLOPS/s)",HIB,79.9,83.7
"VVenC - Video Input: Bosphorus 4K - Video Preset: Faster (FPS)",HIB,2.693,2.672
"Embree - Binary: Pathtracer - Model: Crown (FPS)",HIB,3.5218,3.4542
"Embree - Binary: Pathtracer - Model: Asian Dragon Obj (FPS)",HIB,3.8229,3.8503
"Apache IoTDB - Device Count: 500 - Batch Size Per Write: 100 - Sensor Count: 200 (Latency)",HIB,212.43,198.41
"Apache IoTDB - Device Count: 500 - Batch Size Per Write: 100 - Sensor Count: 200 (point/sec)",HIB,8900311.03,9246224.42
"Embree - Binary: Pathtracer ISPC - Model: Crown (FPS)",HIB,3.7369,3.6962
"Xonotic - Resolution: 1920 x 1080 - Effects Quality: Low (FPS)",HIB,205.6062326,205.4486260
"Apache IoTDB - Device Count: 200 - Batch Size Per Write: 100 - Sensor Count: 500 (Latency)",HIB,550.47,485.93
"Apache IoTDB - Device Count: 200 - Batch Size Per Write: 100 - Sensor Count: 500 (point/sec)",HIB,8609112.97,9394851.37
"OSPRay - Benchmark: particle_volume/pathtracer/real_time (Items/sec)",HIB,52.5904,50.0829
"Embree - Binary: Pathtracer ISPC - Model: Asian Dragon Obj (FPS)",HIB,4.1670,3.9923
"Intel Open Image Denoise - Run: RT.hdr_alb_nrm.3840x2160 - Device: CPU-Only (Images / Sec)",HIB,0.12,0.12
"Intel Open Image Denoise - Run: RT.ldr_alb_nrm.3840x2160 - Device: CPU-Only (Images / Sec)",HIB,0.12,0.12
"NCNN - Target: Vulkan GPU - Model: FastestDet (ms)",LIB,5.66,5.47
"NCNN - Target: Vulkan GPU - Model: vision_transformer (ms)",LIB,240.03,235.51
"NCNN - Target: Vulkan GPU - Model: regnety_400m (ms)",LIB,9.82,10.41
"NCNN - Target: Vulkan GPU - Model: squeezenet_ssd (ms)",LIB,15.97,15.48
"NCNN - Target: Vulkan GPU - Model: yolov4-tiny (ms)",LIB,39.39,39.17
"NCNN - Target: Vulkan GPU - Model: resnet50 (ms)",LIB,33.18,33.60
"NCNN - Target: Vulkan GPU - Model: alexnet (ms)",LIB,11.67,11.69
"NCNN - Target: Vulkan GPU - Model: resnet18 (ms)",LIB,12.73,12.56
"NCNN - Target: Vulkan GPU - Model: vgg16 (ms)",LIB,97.70,96.26
"NCNN - Target: Vulkan GPU - Model: googlenet (ms)",LIB,16.29,16.19
"NCNN - Target: Vulkan GPU - Model: blazeface (ms)",LIB,0.94,0.96
"NCNN - Target: Vulkan GPU - Model: efficientnet-b0 (ms)",LIB,9.22,9.34
"NCNN - Target: Vulkan GPU - Model: mnasnet (ms)",LIB,5.23,5.26
"NCNN - Target: Vulkan GPU - Model: shufflenet-v2 (ms)",LIB,3.66,3.67
"NCNN - Target: Vulkan GPU-v3-v3 - Model: mobilenet-v3 (ms)",LIB,5.11,5.11
"NCNN - Target: Vulkan GPU-v2-v2 - Model: mobilenet-v2 (ms)",LIB,6.67,6.67
"NCNN - Target: Vulkan GPU - Model: mobilenet (ms)",LIB,28.15,27.38
"OSPRay - Benchmark: particle_volume/scivis/real_time (Items/sec)",HIB,1.37399,1.34467
"NCNN - Target: CPU - Model: FastestDet (ms)",LIB,5.39,5.55
"NCNN - Target: CPU - Model: vision_transformer (ms)",LIB,233.96,232.17
"NCNN - Target: CPU - Model: regnety_400m (ms)",LIB,10.03,10.12
"NCNN - Target: CPU - Model: squeezenet_ssd (ms)",LIB,16.55,15.80
"NCNN - Target: CPU - Model: yolov4-tiny (ms)",LIB,38.37,39.31
"NCNN - Target: CPU - Model: resnet50 (ms)",LIB,36.02,34.33
"NCNN - Target: CPU - Model: alexnet (ms)",LIB,11.68,11.64
"NCNN - Target: CPU - Model: resnet18 (ms)",LIB,12.61,12.62
"NCNN - Target: CPU - Model: vgg16 (ms)",LIB,97.42,98.75
"NCNN - Target: CPU - Model: googlenet (ms)",LIB,16.23,16.19
"NCNN - Target: CPU - Model: blazeface (ms)",LIB,0.91,0.93
"NCNN - Target: CPU - Model: efficientnet-b0 (ms)",LIB,9.78,9.43
"NCNN - Target: CPU - Model: mnasnet (ms)",LIB,6.04,4.49
"NCNN - Target: CPU - Model: shufflenet-v2 (ms)",LIB,4.29,3.02
"NCNN - Target: CPU-v3-v3 - Model: mobilenet-v3 (ms)",LIB,5.14,4.31
"NCNN - Target: CPU-v2-v2 - Model: mobilenet-v2 (ms)",LIB,6.69,6.15
"NCNN - Target: CPU - Model: mobilenet (ms)",LIB,25.93,27.68
"Embree - Binary: Pathtracer - Model: Asian Dragon (FPS)",HIB,4.2183,4.1998
"SVT-AV1 - Encoder Mode: Preset 4 - Input: Bosphorus 4K (FPS)",HIB,1.092,0.948
"VVenC - Video Input: Bosphorus 1080p - Video Preset: Fast (FPS)",HIB,3.905,3.790
"SQLite - Threads / Copies: 4 (sec)",LIB,125.830,173.045
"SQLite - Threads / Copies: 2 (sec)",LIB,123.465,170.014
"Embree - Binary: Pathtracer ISPC - Model: Asian Dragon (FPS)",HIB,4.7883,4.7636
"Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,764.2676,614.6793
"Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,2.6677,3.2461
"libxsmm - M N K: 64 (GFLOPS/s)",HIB,90.9,90.8
"Apache Cassandra - Test: Writes (Op/s)",HIB,26422,26438
"Z3 Theorem Prover - SMT File: 2.smt2 (sec)",LIB,130.941,131.405
"libxsmm - M N K: 32 (GFLOPS/s)",HIB,47.7,48.0
"OSPRay - Benchmark: particle_volume/ao/real_time (Items/sec)",HIB,1.49334,1.3692
"Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,93.8482,58.2368
"Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,21.2985,34.3231
"Apache IoTDB - Device Count: 500 - Batch Size Per Write: 1 - Sensor Count: 500 (Latency)",HIB,75.4,70.46
"Apache IoTDB - Device Count: 500 - Batch Size Per Write: 1 - Sensor Count: 500 (point/sec)",HIB,611157.73,637041.62
"OSPRay - Benchmark: gravity_spheres_volume/dim_512/scivis/real_time (Items/sec)",HIB,0.622182,0.709986
"Apache IoTDB - Device Count: 100 - Batch Size Per Write: 100 - Sensor Count: 500 (Latency)",HIB,342.21,387.15
"Apache IoTDB - Device Count: 100 - Batch Size Per Write: 100 - Sensor Count: 500 (point/sec)",HIB,13467917.31,12006039.14
"Redis 7.0.12 + memtier_benchmark - Protocol: Redis - Clients: 500 - Set To Get Ratio: 1:10 (Ops/sec)",HIB,914462.02,1253523.69
"Redis 7.0.12 + memtier_benchmark - Protocol: Redis - Clients: 500 - Set To Get Ratio: 1:5 (Ops/sec)",HIB,890374.23,1248610.70
"Memcached - Set To Get Ratio: 1:5 (Ops/sec)",HIB,525368.39,518308.20
"Redis 7.0.12 + memtier_benchmark - Protocol: Redis - Clients: 50 - Set To Get Ratio: 1:10 (Ops/sec)",HIB,1109812.44,1455171.86
"Redis 7.0.12 + memtier_benchmark - Protocol: Redis - Clients: 100 - Set To Get Ratio: 1:10 (Ops/sec)",HIB,1028641.19,1377833.48
"Redis 7.0.12 + memtier_benchmark - Protocol: Redis - Clients: 100 - Set To Get Ratio: 1:5 (Ops/sec)",HIB,1016703.27,1372033.18
"Redis 7.0.12 + memtier_benchmark - Protocol: Redis - Clients: 50 - Set To Get Ratio: 1:5 (Ops/sec)",HIB,1039311.12,1398883.01
"Memcached - Set To Get Ratio: 1:10 (Ops/sec)",HIB,502050.43,486807.49
"Memcached - Set To Get Ratio: 1:100 (Ops/sec)",HIB,496309.76,485922.63
"OSPRay - Benchmark: gravity_spheres_volume/dim_512/ao/real_time (Items/sec)",HIB,0.745146,0.734783
"SVT-AV1 - Encoder Mode: Preset 8 - Input: Bosphorus 4K (FPS)",HIB,9.490,9.436
"Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,30.5398,30.5664
"Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,65.4250,65.3564
"VVenC - Video Input: Bosphorus 1080p - Video Preset: Faster (FPS)",HIB,9.882,9.868
"Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,211.9830,179.0772
"Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,9.4553,11.1719
"OSPRay - Benchmark: gravity_spheres_volume/dim_512/pathtracer/real_time (Items/sec)",HIB,1.06164,1.012953
"SQLite - Threads / Copies: 1 (sec)",LIB,30.327,88.585
"Apache IoTDB - Device Count: 200 - Batch Size Per Write: 100 - Sensor Count: 200 (Latency)",HIB,144.53,143.24
"Apache IoTDB - Device Count: 200 - Batch Size Per Write: 100 - Sensor Count: 200 (point/sec)",HIB,12613348.93,12464073
"Neural Magic DeepSparse - Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,669.1809,628.3639
"Neural Magic DeepSparse - Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,2.9815,3.2320
"Neural Magic DeepSparse - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,979.1797,835.8517
"Neural Magic DeepSparse - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,2.0309,2.3883
"Neural Magic DeepSparse - Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,244.5617,245.6430
"Neural Magic DeepSparse - Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,8.3009,8.2832
"Neural Magic DeepSparse - Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,69.5593,70.8213
"Neural Magic DeepSparse - Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,28.9185,28.4640
"dav1d - Video Input: Summer Nature 4K (FPS)",HIB,67.01,66.38
"Neural Magic DeepSparse - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,855.6769,864.9932
"Neural Magic DeepSparse - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,2.3527,2.3352
"dav1d - Video Input: Chimera 1080p 10-bit (FPS)",HIB,191.30,190.87
"Z3 Theorem Prover - SMT File: 1.smt2 (sec)",LIB,43.973,43.419
"Neural Magic DeepSparse - Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,116.2683,98.7143
"Neural Magic DeepSparse - Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,17.5124,20.7264
"Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,162.1647,154.2586
"Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,12.5441,12.9502
"Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,137.9489,139.0475
"Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,14.6720,14.6069
"Neural Magic DeepSparse - Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,65.9517,68.0003
"Neural Magic DeepSparse - Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,30.5673,29.7603
"Neural Magic DeepSparse - Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,68.0491,69.6181
"Neural Magic DeepSparse - Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,29.6585,28.9622
"Neural Magic DeepSparse - Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,10.2465,10.336
"Neural Magic DeepSparse - Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,196.7843,195.4858
"SVT-AV1 - Encoder Mode: Preset 4 - Input: Bosphorus 1080p (FPS)",HIB,4.260,4.773
"dav1d - Video Input: Chimera 1080p (FPS)",HIB,244.12,249.62
"Opus Codec Encoding - WAV To Opus Encode (sec)",LIB,35.396,35.426
"Apache IoTDB - Device Count: 100 - Batch Size Per Write: 100 - Sensor Count: 200 (Latency)",HIB,107.84,104.43
"Apache IoTDB - Device Count: 100 - Batch Size Per Write: 100 - Sensor Count: 200 (point/sec)",HIB,15017343.49,15526243.84
"QuantLib - (MFLOPS)",HIB,2379.8,2404.8
"Stress-NG - Test: IO_uring (Bogo Ops/s)",HIB,170492.16,182936.68
"Apache IoTDB - Device Count: 500 - Batch Size Per Write: 1 - Sensor Count: 200 (Latency)",HIB,15.75,15.11
"Apache IoTDB - Device Count: 500 - Batch Size Per Write: 1 - Sensor Count: 200 (point/sec)",HIB,1036429.93,1040683.13
"Stress-NG - Test: Malloc (Bogo Ops/s)",HIB,375933.99,434156.10
"Stress-NG - Test: Cloning (Bogo Ops/s)",HIB,669.41,715.58
"Stress-NG - Test: MMAP (Bogo Ops/s)",HIB,20.86,28.46
"Stress-NG - Test: MEMFD (Bogo Ops/s)",HIB,56.59,43.09
"Stress-NG - Test: Zlib (Bogo Ops/s)",HIB,273.05,335.91
"Stress-NG - Test: Pipe (Bogo Ops/s)",HIB,1422109.84,1533355.11
"Stress-NG - Test: Atomic (Bogo Ops/s)",HIB,224.51,249.99
"Stress-NG - Test: NUMA (Bogo Ops/s)",HIB,53.95,60.49
"Stress-NG - Test: Pthread (Bogo Ops/s)",HIB,34974.26,42229.61
"Stress-NG - Test: x86_64 RdRand (Bogo Ops/s)",HIB,3267.31,3134.04
"Stress-NG - Test: Function Call (Bogo Ops/s)",HIB,2058.70,2164.20
"Stress-NG - Test: System V Message Passing (Bogo Ops/s)",HIB,2652462.62,2519916.10
"Stress-NG - Test: Socket Activity (Bogo Ops/s)",HIB,2495.57,2508.63
"Stress-NG - Test: Matrix 3D Math (Bogo Ops/s)",HIB,383.49,396.03
"Liquid-DSP - Threads: 8 - Buffer Length: 256 - Filter Length: 512 (samples/s)",HIB,35719000,36523000
"Stress-NG - Test: Vector Floating Point (Bogo Ops/s)",HIB,7289.32,7877.70
"Liquid-DSP - Threads: 4 - Buffer Length: 256 - Filter Length: 512 (samples/s)",HIB,25830500,25812500
"Liquid-DSP - Threads: 2 - Buffer Length: 256 - Filter Length: 512 (samples/s)",HIB,15179500,15023500
"Liquid-DSP - Threads: 1 - Buffer Length: 256 - Filter Length: 32 (samples/s)",HIB,46516500,46825000
"Stress-NG - Test: AVL Tree (Bogo Ops/s)",HIB,16.41,19.3
"Stress-NG - Test: Floating Point (Bogo Ops/s)",HIB,743.83,762.86
"Stress-NG - Test: Hash (Bogo Ops/s)",HIB,523699.70,638650.51
"Liquid-DSP - Threads: 1 - Buffer Length: 256 - Filter Length: 512 (samples/s)",HIB,7721800,7710850
"Liquid-DSP - Threads: 2 - Buffer Length: 256 - Filter Length: 57 (samples/s)",HIB,73795500,73620500
"Liquid-DSP - Threads: 2 - Buffer Length: 256 - Filter Length: 32 (samples/s)",HIB,85550500,85664000
"Liquid-DSP - Threads: 1 - Buffer Length: 256 - Filter Length: 57 (samples/s)",HIB,43429000,43427500
"Stress-NG - Test: Memory Copying (Bogo Ops/s)",HIB,1078.73,1088.75
"Liquid-DSP - Threads: 8 - Buffer Length: 256 - Filter Length: 32 (samples/s)",HIB,177945000,185540000
"Stress-NG - Test: Vector Shuffle (Bogo Ops/s)",HIB,2431.22,2431.01
"Stress-NG - Test: CPU Cache (Bogo Ops/s)",HIB,929178.43,1153192.75
"Liquid-DSP - Threads: 8 - Buffer Length: 256 - Filter Length: 57 (samples/s)",HIB,140345000,132830000
"Liquid-DSP - Threads: 4 - Buffer Length: 256 - Filter Length: 57 (samples/s)",HIB,119590000,112205000
"Liquid-DSP - Threads: 4 - Buffer Length: 256 - Filter Length: 32 (samples/s)",HIB,140280000,139950000
"Stress-NG - Test: Forking (Bogo Ops/s)",HIB,9551.79,12140.60
"Stress-NG - Test: Mutex (Bogo Ops/s)",HIB,604156.72,694562.47
"Stress-NG - Test: Glibc Qsort Data Sorting (Bogo Ops/s)",HIB,69.13,74.13
"Stress-NG - Test: Matrix Math (Bogo Ops/s)",HIB,17318.7,17116.79
"Stress-NG - Test: CPU Stress (Bogo Ops/s)",HIB,7310.05,7866.4
"Stress-NG - Test: SENDFILE (Bogo Ops/s)",HIB,36779.86,43752.37
"Stress-NG - Test: Crypto (Bogo Ops/s)",HIB,4590.53,5684.53
"Stress-NG - Test: Wide Vector Math (Bogo Ops/s)",HIB,147314.85,148388.79
"Stress-NG - Test: Poll (Bogo Ops/s)",HIB,284300.80,318466.50
"Stress-NG - Test: Glibc C String Functions (Bogo Ops/s)",HIB,2485856.07,2360589.10
"Stress-NG - Test: Fused Multiply-Add (Bogo Ops/s)",HIB,2978232.73,2737483.30
"Stress-NG - Test: Context Switching (Bogo Ops/s)",HIB,705297.96,733269.79
"Stress-NG - Test: Vector Math (Bogo Ops/s)",HIB,12666.19,12444.33
"Stress-NG - Test: Semaphores (Bogo Ops/s)",HIB,3218725.51,3241408.21
"Stress-NG - Test: Futex (Bogo Ops/s)",HIB,486078.68,624014.17
"Apache IoTDB - Device Count: 200 - Batch Size Per Write: 1 - Sensor Count: 500 (Latency)",HIB,29.65,29.75
"Apache IoTDB - Device Count: 200 - Batch Size Per Write: 1 - Sensor Count: 500 (point/sec)",HIB,1333775.59,1298988.31
"Apache IoTDB - Device Count: 200 - Batch Size Per Write: 1 - Sensor Count: 200 (Latency)",HIB,17.34,16.68
"Apache IoTDB - Device Count: 200 - Batch Size Per Write: 1 - Sensor Count: 200 (point/sec)",HIB,816344.2,812170.86
"Apache IoTDB - Device Count: 100 - Batch Size Per Write: 1 - Sensor Count: 500 (Latency)",HIB,34.81,34.48
"Apache IoTDB - Device Count: 100 - Batch Size Per Write: 1 - Sensor Count: 500 (point/sec)",HIB,996242.81,1009840.28
"SVT-AV1 - Encoder Mode: Preset 12 - Input: Bosphorus 4K (FPS)",HIB,35.497,28.978
"SVT-AV1 - Encoder Mode: Preset 13 - Input: Bosphorus 4K (FPS)",HIB,34.049,30.975
"SVT-AV1 - Encoder Mode: Preset 8 - Input: Bosphorus 1080p (FPS)",HIB,35.739,31.014
"Apache IoTDB - Device Count: 100 - Batch Size Per Write: 1 - Sensor Count: 200 (Latency)",HIB,22.62,22.93
"Apache IoTDB - Device Count: 100 - Batch Size Per Write: 1 - Sensor Count: 200 (point/sec)",HIB,529599,524660.18
"dav1d - Video Input: Summer Nature 1080p (FPS)",HIB,273.35,310.94
"vkpeak - fp32-scalar (GFLOPS)",HIB,268.33,268.33
"SVT-AV1 - Encoder Mode: Preset 12 - Input: Bosphorus 1080p (FPS)",HIB,154.597,157.692
"SVT-AV1 - Encoder Mode: Preset 13 - Input: Bosphorus 1080p (FPS)",HIB,202.852,206.769