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
{
"title": "tg",
"last_modified": "2023-11-25 19:43:07",
"description": "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.",
"systems": {
"a": {
"identifier": "a",
"hardware": {
"Processor": "Intel Core i7-1280P @ 4.70GHz (14 Cores \/ 20 Threads)",
"Motherboard": "MSI MS-14C6 (E14C6IMS.115 BIOS)",
"Chipset": "Intel Alder Lake PCH",
"Memory": "16GB",
"Disk": "1024GB Micron_3400_MTFDKBA1T0TFH",
"Graphics": "MSI Intel ADL GT2 15GB (1450MHz)",
"Audio": "Realtek ALC274",
"Network": "Intel Alder Lake-P PCH CNVi WiFi"
},
"software": {
"OS": "Ubuntu 23.10",
"Kernel": "6.5.0-10-generic (x86_64)",
"Desktop": "GNOME Shell 45.0",
"Display Server": "X Server + Wayland",
"OpenGL": "4.6 Mesa 23.2.1-1ubuntu3",
"OpenCL": "OpenCL 3.0",
"Compiler": "GCC 13.2.0",
"File-System": "ext4",
"Screen Resolution": "1920x1080"
},
"user": "phoronix",
"timestamp": "2023-11-25 14:26:15",
"client_version": "10.8.4",
"data": {
"compiler-configuration": "--build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-bootstrap --enable-cet --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,d,fortran,objc,obj-c++,m2 --enable-libphobos-checking=release --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-link-serialization=2 --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-defaulted --enable-offload-targets=nvptx-none=\/build\/gcc-13-XYspKM\/gcc-13-13.2.0\/debian\/tmp-nvptx\/usr,amdgcn-amdhsa=\/build\/gcc-13-XYspKM\/gcc-13-13.2.0\/debian\/tmp-gcn\/usr --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-build-config=bootstrap-lto-lean --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib=auto --with-tune=generic --without-cuda-driver -v",
"cpu-scaling-governor": "intel_pstate powersave (EPP: balance_performance)",
"cpu-microcode": "0x42c",
"cpu-thermald": "2.5.4",
"kernel-extra-details": "Transparent Huge Pages: madvise",
"java": "OpenJDK Runtime Environment (build 17.0.9-ea+6-Ubuntu-1)",
"python": "Python 3.11.6",
"security": "gather_data_sampling: Not affected + itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + retbleed: Not affected + spec_rstack_overflow: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl + spectre_v1: Mitigation of usercopy\/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Enhanced \/ Automatic IBRS IBPB: conditional RSB filling PBRSB-eIBRS: SW sequence + srbds: Not affected + tsx_async_abort: Not affected"
}
},
"b": {
"identifier": "b",
"hardware": {
"Processor": "Intel Core i7-1280P @ 4.70GHz (14 Cores \/ 20 Threads)",
"Motherboard": "MSI MS-14C6 (E14C6IMS.115 BIOS)",
"Chipset": "Intel Alder Lake PCH",
"Memory": "16GB",
"Disk": "1024GB Micron_3400_MTFDKBA1T0TFH",
"Graphics": "MSI Intel ADL GT2 15GB (1450MHz)",
"Audio": "Realtek ALC274",
"Network": "Intel Alder Lake-P PCH CNVi WiFi"
},
"software": {
"OS": "Ubuntu 23.10",
"Kernel": "6.5.0-10-generic (x86_64)",
"Desktop": "GNOME Shell 45.0",
"Display Server": "X Server + Wayland",
"OpenGL": "4.6 Mesa 23.2.1-1ubuntu3",
"OpenCL": "OpenCL 3.0",
"Compiler": "GCC 13.2.0",
"File-System": "ext4",
"Screen Resolution": "1920x1080"
},
"user": "phoronix",
"timestamp": "2023-11-25 17:14:15",
"client_version": "10.8.4",
"data": {
"compiler-configuration": "--build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-bootstrap --enable-cet --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,d,fortran,objc,obj-c++,m2 --enable-libphobos-checking=release --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-link-serialization=2 --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-defaulted --enable-offload-targets=nvptx-none=\/build\/gcc-13-XYspKM\/gcc-13-13.2.0\/debian\/tmp-nvptx\/usr,amdgcn-amdhsa=\/build\/gcc-13-XYspKM\/gcc-13-13.2.0\/debian\/tmp-gcn\/usr --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-build-config=bootstrap-lto-lean --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib=auto --with-tune=generic --without-cuda-driver -v",
"cpu-scaling-governor": "intel_pstate powersave (EPP: balance_performance)",
"cpu-microcode": "0x42c",
"cpu-thermald": "2.5.4",
"kernel-extra-details": "Transparent Huge Pages: madvise",
"java": "OpenJDK Runtime Environment (build 17.0.9-ea+6-Ubuntu-1)",
"python": "Python 3.11.6",
"security": "gather_data_sampling: Not affected + itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + retbleed: Not affected + spec_rstack_overflow: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl + spectre_v1: Mitigation of usercopy\/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Enhanced \/ Automatic IBRS IBPB: conditional RSB filling PBRSB-eIBRS: SW sequence + srbds: Not affected + tsx_async_abort: Not affected"
}
}
},
"results": {
"6ece9809c0d05b3aa76408656012e1d2854ce8ad": {
"identifier": "pts\/arrayfire-1.2.0",
"title": "ArrayFire",
"app_version": "3.9",
"arguments": "blas_cpu",
"description": "Test: BLAS CPU FP32",
"scale": "GFLOPS",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 394.68599999999997862687450833618640899658203125,
"test_run_times": [
33.5499999999999971578290569595992565155029296875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3"
}
}
},
"b": {
"value": 106.2349999999999994315658113919198513031005859375,
"test_run_times": [
33.8900000000000005684341886080801486968994140625
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3"
}
}
}
}
},
"0907a1560e5c52798d2914d696599aa4df306187": {
"identifier": "pts\/pytorch-1.0.0",
"title": "PyTorch",
"app_version": "2.1",
"arguments": "cpu 32 resnet152",
"description": "Device: CPU - Batch Size: 32 - Model: ResNet-152",
"scale": "batches\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 5.4000000000000003552713678800500929355621337890625,
"raw_values": [
5.40316245077000001373335180687718093395233154296875
],
"min_result": [
"5.26"
],
"max_result": [
"7.05"
],
"test_run_times": [
323.8500000000000227373675443232059478759765625
]
},
"b": {
"value": 3.839999999999999857891452847979962825775146484375,
"raw_values": [
3.840491431974200065013747007469646632671356201171875
],
"min_result": [
"3.77"
],
"max_result": [
"5.24"
],
"test_run_times": [
464.3500000000000227373675443232059478759765625
]
}
}
},
"c2e61282c984934f432761184e26030c16efcb9a": {
"identifier": "pts\/pytorch-1.0.0",
"title": "PyTorch",
"app_version": "2.1",
"arguments": "cpu 16 efficientnet_v2_l",
"description": "Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_l",
"scale": "batches\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 3.390000000000000124344978758017532527446746826171875,
"raw_values": [
3.39110972839710012038949571433477103710174560546875
],
"min_result": [
"3.16"
],
"max_result": [
"5.04"
],
"test_run_times": [
529.509999999999990905052982270717620849609375
]
},
"b": {
"value": 2.520000000000000017763568394002504646778106689453125,
"raw_values": [
2.52086177876639982997630795580334961414337158203125
],
"min_result": [
"2.46"
],
"max_result": [
"3.36"
],
"test_run_times": [
684.5700000000000500222085975110530853271484375
]
}
}
},
"9cdeeeb15ee95815eb3af9e1d46e18fa5e4f3555": {
"identifier": "pts\/blender-4.0.0",
"title": "Blender",
"app_version": "4.0",
"arguments": "-b ..\/bmw27_gpu.blend -o output.test -x 1 -F JPEG -f 1 -- --cycles-device CPU",
"description": "Blend File: BMW27 - Compute: CPU-Only",
"scale": "Seconds",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 233.56000000000000227373675443232059478759765625,
"test_run_times": [
234.479999999999989768184605054557323455810546875
]
},
"b": {
"value": 308.05000000000001136868377216160297393798828125,
"test_run_times": [
308.3999999999999772626324556767940521240234375
]
}
}
},
"4c7bf00e1ffdac6120c4e7e06f896a2dcf99c6a6": {
"identifier": "pts\/pytorch-1.0.0",
"title": "PyTorch",
"app_version": "2.1",
"arguments": "cpu 1 resnet50",
"description": "Device: CPU - Batch Size: 1 - Model: ResNet-50",
"scale": "batches\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 20.03999999999999914734871708787977695465087890625,
"raw_values": [
20.037493052557000083879756857641041278839111328125
],
"min_result": [
"17.17"
],
"max_result": [
"35.57"
],
"test_run_times": [
56.9500000000000028421709430404007434844970703125
]
},
"b": {
"value": 15.4700000000000006394884621840901672840118408203125,
"raw_values": [
15.467770860457999759773883852176368236541748046875
],
"min_result": [
"14.08"
],
"max_result": [
"22.48"
],
"test_run_times": [
72.280000000000001136868377216160297393798828125
]
}
}
},
"594d16c50ef13421d29a77ac009ce481ebc2a82c": {
"identifier": "pts\/pytorch-1.0.0",
"title": "PyTorch",
"app_version": "2.1",
"arguments": "cpu 16 resnet50",
"description": "Device: CPU - Batch Size: 16 - Model: ResNet-50",
"scale": "batches\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 13.769999999999999573674358543939888477325439453125,
"raw_values": [
13.7655750791009996447655794327147305011749267578125
],
"min_result": [
"12.94"
],
"max_result": [
"18.53"
],
"test_run_times": [
134.960000000000007958078640513122081756591796875
]
},
"b": {
"value": 10.75,
"raw_values": [
10.7476676121790006845913012512028217315673828125
],
"min_result": [
"10.17"
],
"max_result": [
"15.41"
],
"test_run_times": [
171.81000000000000227373675443232059478759765625
]
}
}
},
"b822f410294900d7f2a8b2854249b31e725cc8e9": {
"identifier": "pts\/pytorch-1.0.0",
"title": "PyTorch",
"app_version": "2.1",
"arguments": "cpu 64 resnet50",
"description": "Device: CPU - Batch Size: 64 - Model: ResNet-50",
"scale": "batches\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 13.7599999999999997868371792719699442386627197265625,
"raw_values": [
13.7565181520909991519374671042896807193756103515625
],
"min_result": [
"13.09"
],
"max_result": [
"18.12"
],
"test_run_times": [
126.6400000000000005684341886080801486968994140625
]
},
"b": {
"value": 10.75,
"raw_values": [
10.754423064621999373002836364321410655975341796875
],
"min_result": [
"10.57"
],
"max_result": [
"15.02"
],
"test_run_times": [
162.409999999999996589394868351519107818603515625
]
}
}
},
"0abf31405b047991c985067ba99ea7917c482689": {
"identifier": "pts\/pytorch-1.0.0",
"title": "PyTorch",
"app_version": "2.1",
"arguments": "cpu 32 resnet50",
"description": "Device: CPU - Batch Size: 32 - Model: ResNet-50",
"scale": "batches\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 13.7799999999999993605115378159098327159881591796875,
"raw_values": [
13.780966954265000623536252533085644245147705078125
],
"min_result": [
"13.15"
],
"max_result": [
"18.24"
],
"test_run_times": [
129
]
},
"b": {
"value": 10.769999999999999573674358543939888477325439453125,
"raw_values": [
10.7742397003600007820978134986944496631622314453125
],
"min_result": [
"10.43"
],
"max_result": [
"14.76"
],
"test_run_times": [
161.3899999999999863575794734060764312744140625
]
}
}
},
"4f2db05f6bebd9b371472ed1afa49f37fc27fa2a": {
"identifier": "pts\/pytorch-1.0.0",
"title": "PyTorch",
"app_version": "2.1",
"arguments": "cpu 16 resnet152",
"description": "Device: CPU - Batch Size: 16 - Model: ResNet-152",
"scale": "batches\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 5.44000000000000039079850466805510222911834716796875,
"raw_values": [
5.442693316460900376796416821889579296112060546875
],
"min_result": [
"5.3"
],
"max_result": [
"7.11"
],
"test_run_times": [
331.6299999999999954525264911353588104248046875
]
},
"b": {
"value": 4.269999999999999573674358543939888477325439453125,
"raw_values": [
4.27053343990410017028125366778112947940826416015625
],
"min_result": [
"4.17"
],
"max_result": [
"5.87"
],
"test_run_times": [
409.31000000000000227373675443232059478759765625
]
}
}
},
"460f3f52d99a6b1222fa6f3c476e002ef5f32c34": {
"identifier": "pts\/pytorch-1.0.0",
"title": "PyTorch",
"app_version": "2.1",
"arguments": "cpu 64 resnet152",
"description": "Device: CPU - Batch Size: 64 - Model: ResNet-152",
"scale": "batches\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 5.45000000000000017763568394002504646778106689453125,
"raw_values": [
5.44912968545320008928456445573829114437103271484375
],
"min_result": [
"5.17"
],
"max_result": [
"7.1"
],
"test_run_times": [
324.470000000000027284841053187847137451171875
]
},
"b": {
"value": 4.29000000000000003552713678800500929355621337890625,
"raw_values": [
4.29394622952319959807709892629645764827728271484375
],
"min_result": [
"4.22"
],
"max_result": [
"5.81"
],
"test_run_times": [
409.779999999999972715158946812152862548828125
]
}
}
},
"0f8d8cb3b9eaa2299a391dfeb4ecf8e83c675ab3": {
"identifier": "pts\/pytorch-1.0.0",
"title": "PyTorch",
"app_version": "2.1",
"arguments": "cpu 1 resnet152",
"description": "Device: CPU - Batch Size: 1 - Model: ResNet-152",
"scale": "batches\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 9.1899999999999995026200849679298698902130126953125,
"raw_values": [
9.1948376883087998834298559813760221004486083984375
],
"min_result": [
"8.48"
],
"max_result": [
"12.97"
],
"test_run_times": [
122.719999999999998863131622783839702606201171875
]
},
"b": {
"value": 7.3300000000000000710542735760100185871124267578125,
"raw_values": [
7.32975822654649977749841127661056816577911376953125
],
"min_result": [
"7.08"
],
"max_result": [
"11.65"
],
"test_run_times": [
153.68999999999999772626324556767940521240234375
]
}
}
},
"06433753eb3461ed54a6c8a439305e4be1795a41": {
"identifier": "pts\/pytorch-1.0.0",
"title": "PyTorch",
"app_version": "2.1",
"arguments": "cpu 1 efficientnet_v2_l",
"description": "Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_l",
"scale": "batches\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 5.519999999999999573674358543939888477325439453125,
"raw_values": [
5.52037941595019976404046246898360550403594970703125
],
"min_result": [
"5.16"
],
"max_result": [
"8.36"
],
"test_run_times": [
199.44999999999998863131622783839702606201171875
]
},
"b": {
"value": 4.4900000000000002131628207280300557613372802734375,
"raw_values": [
4.49079623665870020232659953762777149677276611328125
],
"min_result": [
"4.05"
],
"max_result": [
"6.6"
],
"test_run_times": [
248.509999999999990905052982270717620849609375
]
}
}
},
"ad7acb19d6a0980c1f004560a7f3b80681cfbe0d": {
"identifier": "pts\/pytorch-1.0.0",
"title": "PyTorch",
"app_version": "2.1",
"arguments": "cpu 32 efficientnet_v2_l",
"description": "Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_l",
"scale": "batches\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 3.479999999999999982236431605997495353221893310546875,
"raw_values": [
3.47825150771500002377933924435637891292572021484375
],
"min_result": [
"3.2"
],
"max_result": [
"4.03"
],
"test_run_times": [
509.5
]
},
"b": {
"value": 2.9900000000000002131628207280300557613372802734375,
"raw_values": [
2.989084286554000158275812282226979732513427734375
],
"min_result": [
"2.89"
],
"max_result": [
"4.23"
],
"test_run_times": [
626.6599999999999681676854379475116729736328125
]
}
}
},
"bea8da05927dbb3542ab3e5bba7fe5dc48856f8e": {
"identifier": "pts\/webp2-1.2.1",
"title": "WebP2 Image Encode",
"app_version": "20220823",
"arguments": "-q 100 -effort 5",
"description": "Encode Settings: Quality 100, Compression Effort 5",
"scale": "MP\/s",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 3.600000000000000088817841970012523233890533447265625,
"raw_values": [
3.59820089955019994931717519648373126983642578125
],
"test_run_times": [
6.80999999999999960920149533194489777088165283203125
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-msse4.2 -fno-rtti -O3 -ldl"
}
}
},
"b": {
"value": 3.149999999999999911182158029987476766109466552734375,
"raw_values": [
3.15208825847119999963297232170589268207550048828125
],
"test_run_times": [
7.769999999999999573674358543939888477325439453125
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-msse4.2 -fno-rtti -O3 -ldl"
}
}
}
}
},
"1d8b7a6381195710860ba3c50ce35ece847d32da": {
"identifier": "pts\/pytorch-1.0.0",
"title": "PyTorch",
"app_version": "2.1",
"arguments": "cpu 64 efficientnet_v2_l",
"description": "Device: CPU - Batch Size: 64 - Model: Efficientnet_v2_l",
"scale": "batches\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 3.229999999999999982236431605997495353221893310546875,
"raw_values": [
3.22701399008180001004575387923978269100189208984375
],
"min_result": [
"3.15"
],
"max_result": [
"4.09"
],
"test_run_times": [
538.509999999999990905052982270717620849609375
]
},
"b": {
"value": 2.970000000000000195399252334027551114559173583984375,
"raw_values": [
2.969447289016299951214250540942884981632232666015625
],
"min_result": [
"2.92"
],
"max_result": [
"4.19"
],
"test_run_times": [
627.44000000000005456968210637569427490234375
]
}
}
},
"49466dc998a615ddac81012171c936fe2c827c89": {
"identifier": "pts\/arrayfire-1.2.0",
"title": "ArrayFire",
"app_version": "3.9",
"arguments": "cg_cpu",
"description": "Test: Conjugate Gradient CPU",
"scale": "ms",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 13.4199999999999999289457264239899814128875732421875,
"test_run_times": [
2.279999999999999804600747665972448885440826416015625
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3"
}
}
},
"b": {
"value": 13.1199999999999992184029906638897955417633056640625,
"test_run_times": [
2.5800000000000000710542735760100185871124267578125
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3"
}
}
}
}
},
"2b08a5e27da8049c6deef7d09507ae35dd065613": {
"identifier": "pts\/java-scimark2-1.2.0",
"title": "Java SciMark",
"app_version": "2.2",
"arguments": "TEST_FFT",
"description": "Computational Test: Fast Fourier Transform",
"scale": "Mflops",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 719.9299999999999499777914024889469146728515625
},
"b": {
"value": 725.1200000000000045474735088646411895751953125
}
}
},
"bf81340647b6254688b34103040b1f9985b00386": {
"identifier": "pts\/java-scimark2-1.2.0",
"title": "Java SciMark",
"app_version": "2.2",
"arguments": "TEST_SPARSE",
"description": "Computational Test: Sparse Matrix Multiply",
"scale": "Mflops",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 3708.46999999999979991116560995578765869140625
},
"b": {
"value": 3733.82000000000016370904631912708282470703125
}
}
},
"733bde69edfe2cd8fbeb6bd9782a71247f3c3eef": {
"identifier": "pts\/embree-1.6.1",
"title": "Embree",
"app_version": "4.3",
"arguments": "pathtracer_ispc -c asian_dragon\/asian_dragon.ecs",
"description": "Binary: Pathtracer ISPC - Model: Asian Dragon",
"scale": "Frames Per Second",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 7.14299999999999979394260662957094609737396240234375,
"min_result": [
"7.04"
],
"max_result": [
"7.25"
],
"test_run_times": [
105.8599999999999994315658113919198513031005859375
]
},
"b": {
"value": 7.11099999999999976552089719916693866252899169921875,
"min_result": [
"6.99"
],
"max_result": [
"7.23"
],
"test_run_times": [
106.2000000000000028421709430404007434844970703125
]
}
}
},
"2f250784301bfd32e248cf035206fa092c926f3d": {
"identifier": "pts\/arrayfire-1.2.0",
"title": "ArrayFire",
"app_version": "3.9",
"arguments": "blas_cpu 0 f16",
"description": "Test: BLAS CPU FP16",
"scale": "GFLOPS",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 64.5390000000000014779288903810083866119384765625,
"test_run_times": [
53.00999999999999801048033987171947956085205078125
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3"
}
}
},
"b": {
"value": 64.289500000000003865352482534945011138916015625,
"test_run_times": [
52.659999999999996589394868351519107818603515625
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3"
}
}
}
}
},
"574a081b9ae673c9ae9fb41c5d652a5396c8e699": {
"identifier": "pts\/java-scimark2-1.2.0",
"title": "Java SciMark",
"app_version": "2.2",
"arguments": "TEST_COMPOSITE",
"description": "Computational Test: Composite",
"scale": "Mflops",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 2908.7899999999999636202119290828704833984375,
"test_run_times": [
28.120000000000000994759830064140260219573974609375
]
},
"b": {
"value": 2916.23000000000001818989403545856475830078125,
"test_run_times": [
28.07000000000000028421709430404007434844970703125
]
}
}
},
"d4ab747c6e0dc7a4a90f81193f4d53321656f67a": {
"identifier": "pts\/java-scimark2-1.2.0",
"title": "Java SciMark",
"app_version": "2.2",
"arguments": "TEST_SOR",
"description": "Computational Test: Jacobi Successive Over-Relaxation",
"scale": "Mflops",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 2340.34999999999990905052982270717620849609375
},
"b": {
"value": 2343.92999999999983629095368087291717529296875
}
}
},
"52e9b3b537761a6a934377d6c32a67848b8fe5a0": {
"identifier": "pts\/webp2-1.2.1",
"title": "WebP2 Image Encode",
"app_version": "20220823",
"description": "Encode Settings: Default",
"scale": "MP\/s",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 7.04999999999999982236431605997495353221893310546875,
"raw_values": [
7.0484581497796998661442557931877672672271728515625
],
"test_run_times": [
3.54999999999999982236431605997495353221893310546875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-msse4.2 -fno-rtti -O3 -ldl"
}
}
},
"b": {
"value": 7.04000000000000003552713678800500929355621337890625,
"raw_values": [
7.04225352112680003102695991401560604572296142578125
],
"test_run_times": [
3.54000000000000003552713678800500929355621337890625
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-msse4.2 -fno-rtti -O3 -ldl"
}
}
}
}
},
"008e5eac15325de22fc93962d17bd49ab4609cef": {
"identifier": "pts\/embree-1.6.1",
"title": "Embree",
"app_version": "4.3",
"arguments": "pathtracer_ispc -c crown\/crown.ecs",
"description": "Binary: Pathtracer ISPC - Model: Crown",
"scale": "Frames Per Second",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 5.33659999999999978825826474349014461040496826171875,
"min_result": [
"5.2"
],
"max_result": [
"5.49"
],
"test_run_times": [
139.31999999999999317878973670303821563720703125
]
},
"b": {
"value": 5.3315999999999998948396751075051724910736083984375,
"min_result": [
"5.2"
],
"max_result": [
"5.49"
],
"test_run_times": [
138.409999999999996589394868351519107818603515625
]
}
}
},
"bc7089c548f2f22bc088fe7f65a58ed65ece8cda": {
"identifier": "pts\/java-scimark2-1.2.0",
"title": "Java SciMark",
"app_version": "2.2",
"arguments": "TEST_MONTE",
"description": "Computational Test: Monte Carlo",
"scale": "Mflops",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 1245.279999999999972715158946812152862548828125
},
"b": {
"value": 1246.359999999999899955582804977893829345703125
}
}
},
"593b182b3d63dfc072f5a5b0164386ad039e00cc": {
"identifier": "pts\/java-scimark2-1.2.0",
"title": "Java SciMark",
"app_version": "2.2",
"arguments": "TEST_DENSE",
"description": "Computational Test: Dense LU Matrix Factorization",
"scale": "Mflops",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 6529.9499999999998181010596454143524169921875
},
"b": {
"value": 6531.9499999999998181010596454143524169921875
}
}
},
"8428c1c79d7e8f2f99c001f196a0b9f7c5032d83": {
"identifier": "pts\/webp2-1.2.1",
"title": "WebP2 Image Encode",
"app_version": "20220823",
"arguments": "-q 100 -effort 9",
"description": "Encode Settings: Quality 100, Lossless Compression",
"scale": "MP\/s",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 0.01000000000000000020816681711721685132943093776702880859375,
"raw_values": [
0.01066766231514900027665948556432340410538017749786376953125
],
"test_run_times": [
2249.920000000000072759576141834259033203125
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-msse4.2 -fno-rtti -O3 -ldl"
}
}
},
"b": {
"value": 0.01000000000000000020816681711721685132943093776702880859375,
"raw_values": [
0.00868956632908910071855235202065159683115780353546142578125
],
"test_run_times": [
2762.09999999999990905052982270717620849609375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-msse4.2 -fno-rtti -O3 -ldl"
}
}
}
}
},
"5a9e80d4ba03c8d8797d684ff12cf9cae34c916a": {
"identifier": "pts\/webp2-1.2.1",
"title": "WebP2 Image Encode",
"app_version": "20220823",
"arguments": "-q 95 -effort 7",
"description": "Encode Settings: Quality 95, Compression Effort 7",
"scale": "MP\/s",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 0.040000000000000000832667268468867405317723751068115234375,
"raw_values": [
0.042898279242773999786475513928962755016982555389404296875
],
"test_run_times": [
559.6100000000000136424205265939235687255859375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-msse4.2 -fno-rtti -O3 -ldl"
}
}
},
"b": {
"value": 0.040000000000000000832667268468867405317723751068115234375,
"raw_values": [
0.036319337777407999234835500601548119448125362396240234375
],
"test_run_times": [
660.9600000000000363797880709171295166015625
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-msse4.2 -fno-rtti -O3 -ldl"
}
}
}
}
},
"1de19da70064fa73db2a1fcca2bdd3ac7e07a0b6": {
"identifier": "pts\/webp2-1.2.1",
"title": "WebP2 Image Encode",
"app_version": "20220823",
"arguments": "-q 75 -effort 7",
"description": "Encode Settings: Quality 75, Compression Effort 7",
"scale": "MP\/s",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 0.0899999999999999966693309261245303787291049957275390625,
"raw_values": [
0.09251157358332000313350107489895890466868877410888671875
],
"test_run_times": [
259.55000000000001136868377216160297393798828125
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-msse4.2 -fno-rtti -O3 -ldl"
}
}
},
"b": {
"value": 0.0899999999999999966693309261245303787291049957275390625,
"raw_values": [
0.09128842196551599508236307656261487863957881927490234375
],
"test_run_times": [
263.029999999999972715158946812152862548828125
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-msse4.2 -fno-rtti -O3 -ldl"
}
}
}
}
}
}
}