Tests for a future article. Intel Core i7-1280P testing with a MSI MS-14C6 (E14C6IMS.115 BIOS) and MSI Intel ADL GT2 15GB on Ubuntu 23.10 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 2311250-NE-TG983149007
tg,
"ArrayFire 3.9 - Test: BLAS CPU FP16",
Higher Results Are Better
"a",
"b",
"ArrayFire 3.9 - Test: BLAS CPU FP32",
Higher Results Are Better
"a",
"b",
"ArrayFire 3.9 - Test: Conjugate Gradient CPU",
Lower Results Are Better
"a",
"b",
"Blender 4.0 - Blend File: BMW27 - Compute: CPU-Only",
Lower Results Are Better
"a",
"b",
"Embree 4.3 - Binary: Pathtracer ISPC - Model: Crown",
Higher Results Are Better
"a",
"b",
"Embree 4.3 - Binary: Pathtracer ISPC - Model: Asian Dragon",
Higher Results Are Better
"a",
"b",
"Java SciMark 2.2 - Computational Test: Composite",
Higher Results Are Better
"a",
"b",
"Java SciMark 2.2 - Computational Test: Monte Carlo",
Higher Results Are Better
"a",
"b",
"Java SciMark 2.2 - Computational Test: Fast Fourier Transform",
Higher Results Are Better
"a",
"b",
"Java SciMark 2.2 - Computational Test: Sparse Matrix Multiply",
Higher Results Are Better
"a",
"b",
"Java SciMark 2.2 - Computational Test: Dense LU Matrix Factorization",
Higher Results Are Better
"a",
"b",
"Java SciMark 2.2 - Computational Test: Jacobi Successive Over-Relaxation",
Higher Results Are Better
"a",
"b",
"PyTorch 2.1 - Device: CPU - Batch Size: 1 - Model: ResNet-50",
Higher Results Are Better
"a",20.037493052557
"b",15.467770860458
"PyTorch 2.1 - Device: CPU - Batch Size: 1 - Model: ResNet-152",
Higher Results Are Better
"a",9.1948376883088
"b",7.3297582265465
"PyTorch 2.1 - Device: CPU - Batch Size: 16 - Model: ResNet-50",
Higher Results Are Better
"a",13.765575079101
"b",10.747667612179
"PyTorch 2.1 - Device: CPU - Batch Size: 32 - Model: ResNet-50",
Higher Results Are Better
"a",13.780966954265
"b",10.77423970036
"PyTorch 2.1 - Device: CPU - Batch Size: 64 - Model: ResNet-50",
Higher Results Are Better
"a",13.756518152091
"b",10.754423064622
"PyTorch 2.1 - Device: CPU - Batch Size: 16 - Model: ResNet-152",
Higher Results Are Better
"a",5.4426933164609
"b",4.2705334399041
"PyTorch 2.1 - Device: CPU - Batch Size: 32 - Model: ResNet-152",
Higher Results Are Better
"a",5.40316245077
"b",3.8404914319742
"PyTorch 2.1 - Device: CPU - Batch Size: 64 - Model: ResNet-152",
Higher Results Are Better
"a",5.4491296854532
"b",4.2939462295232
"PyTorch 2.1 - Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_l",
Higher Results Are Better
"a",5.5203794159502
"b",4.4907962366587
"PyTorch 2.1 - Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_l",
Higher Results Are Better
"a",3.3911097283971
"b",2.5208617787664
"PyTorch 2.1 - Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_l",
Higher Results Are Better
"a",3.478251507715
"b",2.989084286554
"PyTorch 2.1 - Device: CPU - Batch Size: 64 - Model: Efficientnet_v2_l",
Higher Results Are Better
"a",3.2270139900818
"b",2.9694472890163
"WebP2 Image Encode 20220823 - Encode Settings: Default",
Higher Results Are Better
"a",7.0484581497797
"b",7.0422535211268
"WebP2 Image Encode 20220823 - Encode Settings: Quality 75, Compression Effort 7",
Higher Results Are Better
"a",0.09251157358332
"b",0.091288421965516
"WebP2 Image Encode 20220823 - Encode Settings: Quality 95, Compression Effort 7",
Higher Results Are Better
"a",0.042898279242774
"b",0.036319337777408
"WebP2 Image Encode 20220823 - Encode Settings: Quality 100, Compression Effort 5",
Higher Results Are Better
"a",3.5982008995502
"b",3.1520882584712
"WebP2 Image Encode 20220823 - Encode Settings: Quality 100, Lossless Compression",
Higher Results Are Better
"a",0.010667662315149
"b",0.0086895663290891