Tests for a future article. Intel Core i7-1185G7 testing with a Dell 0DXP1F (3.7.0 BIOS) and Intel Xe TGL 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 2312224-PTS-TGLDEC9288
tgldec
Tests for a future article. Intel Core i7-1185G7 testing with a Dell 0DXP1F (3.7.0 BIOS) and Intel Xe TGL GT2 15GB on Ubuntu 22.04 via the Phoronix Test Suite.
,,"a","b"
Processor,,Intel Core i7-1185G7 @ 4.80GHz (4 Cores / 8 Threads),Intel Core i7-1185G7 @ 4.80GHz (4 Cores / 8 Threads)
Motherboard,,Dell 0DXP1F (3.7.0 BIOS),Dell 0DXP1F (3.7.0 BIOS)
Chipset,,Intel Tiger Lake-LP,Intel Tiger Lake-LP
Memory,,16GB,16GB
Disk,,Micron 2300 NVMe 512GB,Micron 2300 NVMe 512GB
Graphics,,Intel Xe TGL GT2 15GB (1350MHz),Intel Xe TGL GT2 15GB (1350MHz)
Audio,,Realtek ALC289,Realtek ALC289
Network,,Intel Wi-Fi 6 AX201,Intel Wi-Fi 6 AX201
OS,,Ubuntu 22.04,Ubuntu 22.04
Kernel,,6.2.0-36-generic (x86_64),6.2.0-36-generic (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 11.4.0,GCC 11.4.0
File-System,,ext4,ext4
Screen Resolution,,1920x1200,1920x1200
,,"a","b"
"Xmrig - Variant: KawPow - Hash Count: 1M (H/s)",HIB,1908.5,1911.1
"Xmrig - Variant: Monero - Hash Count: 1M (H/s)",HIB,1904.9,1912.9
"Xmrig - Variant: Wownero - Hash Count: 1M (H/s)",HIB,2646.2,2647.7
"Xmrig - Variant: GhostRider - Hash Count: 1M (H/s)",HIB,405.3,443.1
"Xmrig - Variant: CryptoNight-Heavy - Hash Count: 1M (H/s)",HIB,1921.1,1913.4
"Xmrig - Variant: CryptoNight-Femto UPX2 - Hash Count: 1M (H/s)",HIB,1902.6,1907.9
"LeelaChessZero - Backend: BLAS (Nodes/s)",HIB,61,62
"LeelaChessZero - Backend: Eigen (Nodes/s)",HIB,51,52
"Neural Magic DeepSparse - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,3.9165,3.8826
"Neural Magic DeepSparse - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,510.1389,514.3343
"Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,127.083,126.7496
"Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,15.7028,15.7456
"Neural Magic DeepSparse - Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,54.4523,54.5005
"Neural Magic DeepSparse - Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,36.6899,36.6402
"Neural Magic DeepSparse - Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,307.9229,307.5055
"Neural Magic DeepSparse - Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,6.467,6.476
"Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,22.1762,23.4406
"Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,90.1433,85.2818
"Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,4.3093,4.3051
"Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,463.8923,461.7999
"Neural Magic DeepSparse - Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,54.2106,53.7709
"Neural Magic DeepSparse - Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,36.8572,37.1625
"Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,22.285,22.9344
"Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,89.7187,87.1754
"Neural Magic DeepSparse - Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,29.973,29.3696
"Neural Magic DeepSparse - Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,66.6604,68.0028
"Neural Magic DeepSparse - Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,6.6146,6.62
"Neural Magic DeepSparse - Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,302.3134,302.07
"Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,55.5425,55.3026
"Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,35.9636,36.1024
"Neural Magic DeepSparse - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,3.7221,3.6422
"Neural Magic DeepSparse - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,537.2767,544.8737
"SVT-AV1 - Encoder Mode: Preset 4 - Input: Bosphorus 4K (FPS)",HIB,1.382,1.376
"SVT-AV1 - Encoder Mode: Preset 8 - Input: Bosphorus 4K (FPS)",HIB,11.352,11.359
"SVT-AV1 - Encoder Mode: Preset 12 - Input: Bosphorus 4K (FPS)",HIB,43.029,41.469
"SVT-AV1 - Encoder Mode: Preset 13 - Input: Bosphorus 4K (FPS)",HIB,43.944,44.422
"SVT-AV1 - Encoder Mode: Preset 4 - Input: Bosphorus 1080p (FPS)",HIB,5.332,5.449
"SVT-AV1 - Encoder Mode: Preset 8 - Input: Bosphorus 1080p (FPS)",HIB,37.936,42.174
"SVT-AV1 - Encoder Mode: Preset 12 - Input: Bosphorus 1080p (FPS)",HIB,194.342,222.463
"SVT-AV1 - Encoder Mode: Preset 13 - Input: Bosphorus 1080p (FPS)",HIB,287.019,285.677
"ScyllaDB - Test: Writes (Op/s)",HIB,42920,46001