Tests for a future article. AMD EPYC 8534P 64-Core testing with a AMD Cinnabar (RCB1009C BIOS) and ASPEED 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 2403268-NE-EPYCSIENA58
{
"title": "epyc siena",
"last_modified": "2024-03-26 20:04:43",
"description": "Tests for a future article. AMD EPYC 8534P 64-Core testing with a AMD Cinnabar (RCB1009C BIOS) and ASPEED on Ubuntu 23.10 via the Phoronix Test Suite.",
"systems": {
"a": {
"identifier": "a",
"hardware": {
"Processor": "AMD EPYC 8534P 64-Core @ 2.30GHz (64 Cores \/ 128 Threads)",
"Motherboard": "AMD Cinnabar (RCB1009C BIOS)",
"Chipset": "AMD Device 14a4",
"Memory": "6 x 32GB DRAM-4800MT\/s Samsung M321R4GA0BB0-CQKMG",
"Disk": "3201GB Micron_7450_MTFDKCB3T2TFS + 2000GB Corsair MP700",
"Graphics": "ASPEED",
"Network": "2 x Broadcom NetXtreme BCM5720 PCIe"
},
"software": {
"OS": "Ubuntu 23.10",
"Kernel": "6.8.1-060801-generic (x86_64)",
"Desktop": "GNOME Shell 45.2",
"Display Server": "X Server 1.21.1.7",
"Compiler": "GCC 13.2.0",
"File-System": "ext4",
"Screen Resolution": "1920x1200"
},
"user": "phoronix",
"timestamp": "2024-03-26 17:35:29",
"client_version": "10.8.4",
"data": {
"cpu-scaling-governor": "acpi-cpufreq performance (Boost: Enabled)",
"cpu-microcode": "0xaa00212",
"kernel-extra-details": "Transparent Huge Pages: madvise",
"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 + reg_file_data_sampling: Not affected + retbleed: Not affected + spec_rstack_overflow: Mitigation of Safe RET + 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 STIBP: always-on RSB filling PBRSB-eIBRS: Not affected + srbds: Not affected + tsx_async_abort: Not affected"
}
},
"b": {
"identifier": "b",
"hardware": {
"Processor": "AMD EPYC 8534P 64-Core @ 2.30GHz (64 Cores \/ 128 Threads)",
"Motherboard": "AMD Cinnabar (RCB1009C BIOS)",
"Chipset": "AMD Device 14a4",
"Memory": "6 x 32GB DRAM-4800MT\/s Samsung M321R4GA0BB0-CQKMG",
"Disk": "3201GB Micron_7450_MTFDKCB3T2TFS + 2000GB Corsair MP700",
"Graphics": "ASPEED",
"Network": "2 x Broadcom NetXtreme BCM5720 PCIe"
},
"software": {
"OS": "Ubuntu 23.10",
"Kernel": "6.8.1-060801-generic (x86_64)",
"Desktop": "GNOME Shell 45.2",
"Display Server": "X Server 1.21.1.7",
"Compiler": "GCC 13.2.0",
"File-System": "ext4",
"Screen Resolution": "1920x1200"
},
"user": "phoronix",
"timestamp": "2024-03-26 19:11:26",
"client_version": "10.8.4",
"data": {
"cpu-scaling-governor": "acpi-cpufreq performance (Boost: Enabled)",
"cpu-microcode": "0xaa00212",
"kernel-extra-details": "Transparent Huge Pages: madvise",
"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 + reg_file_data_sampling: Not affected + retbleed: Not affected + spec_rstack_overflow: Mitigation of Safe RET + 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 STIBP: always-on RSB filling PBRSB-eIBRS: Not affected + srbds: Not affected + tsx_async_abort: Not affected"
}
}
},
"results": {
"801cae2e8025c5598601ed7196f53697d6cdd87e": {
"identifier": "pts\/tensorflow-2.2.0",
"title": "TensorFlow",
"app_version": "2.16.1",
"arguments": "--device cpu --batch_size=256 --model=vgg16",
"description": "Device: CPU - Batch Size: 256 - Model: VGG-16",
"scale": "images\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 45.780000000000001136868377216160297393798828125,
"raw_values": [
45.77000000000000312638803734444081783294677734375,
45.78999999999999914734871708787977695465087890625,
45.77000000000000312638803734444081783294677734375
],
"test_run_times": [
619.55999999999994543031789362430572509765625,
619.73000000000001818989403545856475830078125,
619.94000000000005456968210637569427490234375
]
},
"b": {
"value": 45.71000000000000085265128291212022304534912109375,
"test_run_times": [
620.3700000000000045474735088646411895751953125
]
}
}
},
"b24071a13173fed1d53bd54c5c89d56a1073ff7d": {
"identifier": "pts\/tensorflow-2.2.0",
"title": "TensorFlow",
"app_version": "2.16.1",
"arguments": "--device cpu --batch_size=512 --model=resnet50",
"description": "Device: CPU - Batch Size: 512 - Model: ResNet-50",
"scale": "images\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 104.530000000000001136868377216160297393798828125,
"test_run_times": [
549.26999999999998181010596454143524169921875
]
},
"b": {
"value": 104.6099999999999994315658113919198513031005859375,
"test_run_times": [
548.8799999999999954525264911353588104248046875
]
}
}
},
"27728d5ccf6d68a6274e3d800a76cbeee3a59a98": {
"identifier": "pts\/tensorflow-2.2.0",
"title": "TensorFlow",
"app_version": "2.16.1",
"arguments": "--device cpu --batch_size=64 --model=vgg16",
"description": "Device: CPU - Batch Size: 64 - Model: VGG-16",
"scale": "images\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 44.68999999999999772626324556767940521240234375,
"raw_values": [
44.7000000000000028421709430404007434844970703125,
44.67999999999999971578290569595992565155029296875,
44.67999999999999971578290569595992565155029296875
],
"test_run_times": [
160.909999999999996589394868351519107818603515625,
160.94999999999998863131622783839702606201171875,
161.020000000000010231815394945442676544189453125
]
},
"b": {
"value": 44.7000000000000028421709430404007434844970703125,
"test_run_times": [
160.8799999999999954525264911353588104248046875
]
}
}
},
"c79954d082be150cefddf4af1ec61f414286b450": {
"identifier": "pts\/tensorflow-2.2.0",
"title": "TensorFlow",
"app_version": "2.16.1",
"arguments": "--device cpu --batch_size=256 --model=resnet50",
"description": "Device: CPU - Batch Size: 256 - Model: ResNet-50",
"scale": "images\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 101.9200000000000017053025658242404460906982421875,
"test_run_times": [
283.990000000000009094947017729282379150390625
]
},
"b": {
"value": 101.7300000000000039790393202565610408782958984375,
"test_run_times": [
284.3999999999999772626324556767940521240234375
]
}
}
},
"458a4eb2c6c84b80913e52a3b3e727db73a5af11": {
"identifier": "pts\/blender-4.1.0",
"title": "Blender",
"app_version": "4.1",
"arguments": "-b ..\/barbershop_interior_gpu.blend -o output.test -x 1 -F JPEG -f 1 -- --cycles-device CPU",
"description": "Blend File: Barbershop - Compute: CPU-Only",
"scale": "Seconds",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 230.1299999999999954525264911353588104248046875,
"test_run_times": [
232.460000000000007958078640513122081756591796875
]
},
"b": {
"value": 229.770000000000010231815394945442676544189453125,
"test_run_times": [
232.090000000000003410605131648480892181396484375
]
}
}
},
"5271aa1559827b988959a00c9654f9dec12c83dd": {
"identifier": "pts\/tensorflow-2.2.0",
"title": "TensorFlow",
"app_version": "2.16.1",
"arguments": "--device cpu --batch_size=512 --model=googlenet",
"description": "Device: CPU - Batch Size: 512 - Model: GoogLeNet",
"scale": "images\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 326.6299999999999954525264911353588104248046875,
"test_run_times": [
177.719999999999998863131622783839702606201171875
]
},
"b": {
"value": 326.6000000000000227373675443232059478759765625,
"test_run_times": [
177.770000000000010231815394945442676544189453125
]
}
}
},
"d8cbe80fca45933149672c23d1c95cbdab4d8ca5": {
"identifier": "pts\/tensorflow-2.2.0",
"title": "TensorFlow",
"app_version": "2.16.1",
"arguments": "--device cpu --batch_size=32 --model=vgg16",
"description": "Device: CPU - Batch Size: 32 - Model: VGG-16",
"scale": "images\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 42.82000000000000028421709430404007434844970703125,
"raw_values": [
42.82000000000000028421709430404007434844970703125,
42.78999999999999914734871708787977695465087890625,
42.840000000000003410605131648480892181396484375
],
"test_run_times": [
85.3599999999999994315658113919198513031005859375,
85.400000000000005684341886080801486968994140625,
85.349999999999994315658113919198513031005859375
]
},
"b": {
"value": 42.92999999999999971578290569595992565155029296875,
"test_run_times": [
85.2000000000000028421709430404007434844970703125
]
}
}
},
"29ad2dd362dad2842eaa589bcb10d92457d4742b": {
"identifier": "pts\/tensorflow-2.2.0",
"title": "TensorFlow",
"app_version": "2.16.1",
"arguments": "--device cpu --batch_size=16 --model=vgg16",
"description": "Device: CPU - Batch Size: 16 - Model: VGG-16",
"scale": "images\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 39.780000000000001136868377216160297393798828125,
"raw_values": [
39.85000000000000142108547152020037174224853515625,
39.78999999999999914734871708787977695465087890625,
39.68999999999999772626324556767940521240234375
],
"test_run_times": [
47.219999999999998863131622783839702606201171875,
47.2999999999999971578290569595992565155029296875,
47.4200000000000017053025658242404460906982421875
]
},
"b": {
"value": 39.78999999999999914734871708787977695465087890625,
"test_run_times": [
47.31000000000000227373675443232059478759765625
]
}
}
},
"f45c09499237f1715f224cec3778b8e2b561e26b": {
"identifier": "pts\/tensorflow-2.2.0",
"title": "TensorFlow",
"app_version": "2.16.1",
"arguments": "--device cpu --batch_size=256 --model=googlenet",
"description": "Device: CPU - Batch Size: 256 - Model: GoogLeNet",
"scale": "images\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 320.31000000000000227373675443232059478759765625,
"test_run_times": [
92.530000000000001136868377216160297393798828125
]
},
"b": {
"value": 320.23000000000001818989403545856475830078125,
"test_run_times": [
92.5100000000000051159076974727213382720947265625
]
}
}
},
"c2b4c32d69dc5fddfa4829c640df8922cbe2fa37": {
"identifier": "pts\/tensorflow-2.2.0",
"title": "TensorFlow",
"app_version": "2.16.1",
"arguments": "--device cpu --batch_size=64 --model=resnet50",
"description": "Device: CPU - Batch Size: 64 - Model: ResNet-50",
"scale": "images\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 89.840000000000003410605131648480892181396484375,
"test_run_times": [
83.8299999999999982946974341757595539093017578125
]
},
"b": {
"value": 89.5100000000000051159076974727213382720947265625,
"test_run_times": [
84.090000000000003410605131648480892181396484375
]
}
}
},
"30a7337e8926a086e67a974609766f8885e04e46": {
"identifier": "pts\/blender-4.1.0",
"title": "Blender",
"app_version": "4.1",
"arguments": "-b ..\/pavillon_barcelone_gpu.blend -o output.test -x 1 -F JPEG -f 1 -- --cycles-device CPU",
"description": "Blend File: Pabellon Barcelona - Compute: CPU-Only",
"scale": "Seconds",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 81.1299999999999954525264911353588104248046875,
"test_run_times": [
81.840000000000003410605131648480892181396484375
]
},
"b": {
"value": 80.9800000000000039790393202565610408782958984375,
"test_run_times": [
81.6700000000000017053025658242404460906982421875
]
}
}
},
"d642e29ba0ab924a63605dc5d18ef3966c809dce": {
"identifier": "pts\/blender-4.1.0",
"title": "Blender",
"app_version": "4.1",
"arguments": "-b ..\/classroom_gpu.blend -o output.test -x 1 -F JPEG -f 1 -- --cycles-device CPU",
"description": "Blend File: Classroom - Compute: CPU-Only",
"scale": "Seconds",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 64.849999999999994315658113919198513031005859375,
"test_run_times": [
65.340000000000003410605131648480892181396484375
]
},
"b": {
"value": 64.68000000000000682121026329696178436279296875,
"test_run_times": [
65.1700000000000017053025658242404460906982421875
]
}
}
},
"5c98d60e307e91e3fa4a166cb951aedf30820571": {
"identifier": "pts\/tensorflow-2.2.0",
"title": "TensorFlow",
"app_version": "2.16.1",
"arguments": "--device cpu --batch_size=512 --model=alexnet",
"description": "Device: CPU - Batch Size: 512 - Model: AlexNet",
"scale": "images\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 926.490000000000009094947017729282379150390625,
"test_run_times": [
63.47999999999999687361196265555918216705322265625
]
},
"b": {
"value": 924.6100000000000136424205265939235687255859375,
"test_run_times": [
63.57000000000000028421709430404007434844970703125
]
}
}
},
"553578ea95c8cd321f02803aae717264cb615497": {
"identifier": "pts\/tensorflow-2.2.0",
"title": "TensorFlow",
"app_version": "2.16.1",
"arguments": "--device cpu --batch_size=32 --model=resnet50",
"description": "Device: CPU - Batch Size: 32 - Model: ResNet-50",
"scale": "images\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 79.5400000000000062527760746888816356658935546875,
"test_run_times": [
49.36999999999999744204615126363933086395263671875
]
},
"b": {
"value": 78.849999999999994315658113919198513031005859375,
"test_run_times": [
49.75
]
}
}
},
"9974b636362d9b68a14abd18b674acca424c3a28": {
"identifier": "pts\/blender-4.1.0",
"title": "Blender",
"app_version": "4.1",
"arguments": "-b ..\/junkshop.blend -o output.test -x 1 -F JPEG -f 1 -- --cycles-device CPU",
"description": "Blend File: Junkshop - Compute: CPU-Only",
"scale": "Seconds",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 34.32000000000000028421709430404007434844970703125,
"test_run_times": [
35.0799999999999982946974341757595539093017578125
]
},
"b": {
"value": 34.32000000000000028421709430404007434844970703125,
"test_run_times": [
35.03999999999999914734871708787977695465087890625
]
}
}
},
"3fc0ca1d5a0746bef2ec915696cd1e7e450f0486": {
"identifier": "pts\/tensorflow-2.2.0",
"title": "TensorFlow",
"app_version": "2.16.1",
"arguments": "--device cpu --batch_size=256 --model=alexnet",
"description": "Device: CPU - Batch Size: 256 - Model: AlexNet",
"scale": "images\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 887.98000000000001818989403545856475830078125,
"test_run_times": [
34.31000000000000227373675443232059478759765625
]
},
"b": {
"value": 889.0900000000000318323145620524883270263671875,
"test_run_times": [
34.27000000000000312638803734444081783294677734375
]
}
}
},
"e14b90554ad557bd8220d6925e62f507c49196e0": {
"identifier": "pts\/blender-4.1.0",
"title": "Blender",
"app_version": "4.1",
"arguments": "-b ..\/fishy_cat_gpu.blend -o output.test -x 1 -F JPEG -f 1 -- --cycles-device CPU",
"description": "Blend File: Fishy Cat - Compute: CPU-Only",
"scale": "Seconds",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 32.96000000000000085265128291212022304534912109375,
"test_run_times": [
33.780000000000001136868377216160297393798828125
]
},
"b": {
"value": 32.71000000000000085265128291212022304534912109375,
"test_run_times": [
33.53999999999999914734871708787977695465087890625
]
}
}
},
"113aa8ffcc7b9a5e5921242a3c219cbcf10a56c1": {
"identifier": "pts\/tensorflow-2.2.0",
"title": "TensorFlow",
"app_version": "2.16.1",
"arguments": "--device cpu --batch_size=16 --model=resnet50",
"description": "Device: CPU - Batch Size: 16 - Model: ResNet-50",
"scale": "images\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 64.2900000000000062527760746888816356658935546875,
"test_run_times": [
32.3299999999999982946974341757595539093017578125
]
},
"b": {
"value": 63.5499999999999971578290569595992565155029296875,
"test_run_times": [
32.590000000000003410605131648480892181396484375
]
}
}
},
"756b849822aa6cfd1f7ea7544eee95ad83059012": {
"identifier": "pts\/tensorflow-2.2.0",
"title": "TensorFlow",
"app_version": "2.16.1",
"arguments": "--device cpu --batch_size=64 --model=googlenet",
"description": "Device: CPU - Batch Size: 64 - Model: GoogLeNet",
"scale": "images\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 285.8500000000000227373675443232059478759765625,
"test_run_times": [
28.559999999999998721023075631819665431976318359375
]
},
"b": {
"value": 284.3999999999999772626324556767940521240234375,
"test_run_times": [
28.769999999999999573674358543939888477325439453125
]
}
}
},
"6fa0bb21f313981869d5b7153599c8cd97c5852a": {
"identifier": "pts\/blender-4.1.0",
"title": "Blender",
"app_version": "4.1",
"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": 26.0799999999999982946974341757595539093017578125,
"test_run_times": [
27.190000000000001278976924368180334568023681640625
]
},
"b": {
"value": 25.82000000000000028421709430404007434844970703125,
"test_run_times": [
26.32000000000000028421709430404007434844970703125
]
}
}
},
"c3b5387998e4006084a331673013309ebc420552": {
"identifier": "pts\/tensorflow-2.2.0",
"title": "TensorFlow",
"app_version": "2.16.1",
"arguments": "--device cpu --batch_size=1 --model=vgg16",
"description": "Device: CPU - Batch Size: 1 - Model: VGG-16",
"scale": "images\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 11.4000000000000003552713678800500929355621337890625,
"raw_values": [
11.339999999999999857891452847979962825775146484375,
11.4199999999999999289457264239899814128875732421875,
11.42999999999999971578290569595992565155029296875
],
"test_run_times": [
12.6300000000000007815970093361102044582366943359375,
12.3900000000000005684341886080801486968994140625,
12.3900000000000005684341886080801486968994140625
]
},
"b": {
"value": 11.42999999999999971578290569595992565155029296875,
"test_run_times": [
12.4199999999999999289457264239899814128875732421875
]
}
}
},
"fbe5c59152314e76bd9f9138ab14c06003fca508": {
"identifier": "pts\/tensorflow-2.2.0",
"title": "TensorFlow",
"app_version": "2.16.1",
"arguments": "--device cpu --batch_size=32 --model=googlenet",
"description": "Device: CPU - Batch Size: 32 - Model: GoogLeNet",
"scale": "images\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 249.1200000000000045474735088646411895751953125,
"test_run_times": [
17.949999999999999289457264239899814128875732421875
]
},
"b": {
"value": 249.770000000000010231815394945442676544189453125,
"test_run_times": [
17.92999999999999971578290569595992565155029296875
]
}
}
},
"08449982a4f5f924d45208f47b9d8c62067b2e23": {
"identifier": "pts\/tensorflow-2.2.0",
"title": "TensorFlow",
"app_version": "2.16.1",
"arguments": "--device cpu --batch_size=16 --model=alexnet",
"description": "Device: CPU - Batch Size: 16 - Model: AlexNet",
"scale": "images\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 349.1499999999999772626324556767940521240234375,
"raw_values": [
349.970000000000027284841053187847137451171875,
349.1299999999999954525264911353588104248046875,
348.3500000000000227373675443232059478759765625
],
"test_run_times": [
7.45000000000000017763568394002504646778106689453125,
7.45999999999999996447286321199499070644378662109375,
7.480000000000000426325641456060111522674560546875
]
},
"b": {
"value": 347.82999999999998408384271897375583648681640625,
"test_run_times": [
7.5
]
}
}
},
"1eff874d2ed99fbec15252604d5788236f12724f": {
"identifier": "pts\/tensorflow-2.2.0",
"title": "TensorFlow",
"app_version": "2.16.1",
"arguments": "--device cpu --batch_size=1 --model=resnet50",
"description": "Device: CPU - Batch Size: 1 - Model: ResNet-50",
"scale": "images\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 10.9000000000000003552713678800500929355621337890625,
"test_run_times": [
14.6500000000000003552713678800500929355621337890625
]
},
"b": {
"value": 10.980000000000000426325641456060111522674560546875,
"test_run_times": [
14.589999999999999857891452847979962825775146484375
]
}
}
},
"0c7ca7413dad7058da6c1b7ecf451e37c79a852f": {
"identifier": "pts\/tensorflow-2.2.0",
"title": "TensorFlow",
"app_version": "2.16.1",
"arguments": "--device cpu --batch_size=16 --model=googlenet",
"description": "Device: CPU - Batch Size: 16 - Model: GoogLeNet",
"scale": "images\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 199.740000000000009094947017729282379150390625,
"test_run_times": [
12.519999999999999573674358543939888477325439453125
]
},
"b": {
"value": 200.099999999999994315658113919198513031005859375,
"test_run_times": [
12.4900000000000002131628207280300557613372802734375
]
}
}
},
"cc9e31e984b8806636e79ff6e5e21c1a6f766e29": {
"identifier": "pts\/tensorflow-2.2.0",
"title": "TensorFlow",
"app_version": "2.16.1",
"arguments": "--device cpu --batch_size=64 --model=alexnet",
"description": "Device: CPU - Batch Size: 64 - Model: AlexNet",
"scale": "images\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 704.029999999999972715158946812152862548828125,
"test_run_times": [
12.519999999999999573674358543939888477325439453125
]
},
"b": {
"value": 703.0800000000000409272615797817707061767578125,
"test_run_times": [
12.480000000000000426325641456060111522674560546875
]
}
}
},
"4aa2a8dc9d9beef6165ea03da7a36fbc2fc7b3af": {
"identifier": "pts\/tensorflow-2.2.0",
"title": "TensorFlow",
"app_version": "2.16.1",
"arguments": "--device cpu --batch_size=1 --model=alexnet",
"description": "Device: CPU - Batch Size: 1 - Model: AlexNet",
"scale": "images\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 34.38000000000000255795384873636066913604736328125,
"raw_values": [
34.49000000000000198951966012828052043914794921875,
34.32000000000000028421709430404007434844970703125,
34.340000000000003410605131648480892181396484375
],
"test_run_times": [
5.53000000000000024868995751603506505489349365234375,
5.54999999999999982236431605997495353221893310546875,
5.54999999999999982236431605997495353221893310546875
]
},
"b": {
"value": 34.42999999999999971578290569595992565155029296875,
"test_run_times": [
5.55999999999999960920149533194489777088165283203125
]
}
}
},
"4042d31bc5aa3c11c217e669c15bfcdfecd2af39": {
"identifier": "pts\/tensorflow-2.2.0",
"title": "TensorFlow",
"app_version": "2.16.1",
"arguments": "--device cpu --batch_size=32 --model=alexnet",
"description": "Device: CPU - Batch Size: 32 - Model: AlexNet",
"scale": "images\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 529.3600000000000136424205265939235687255859375,
"test_run_times": [
9.1099999999999994315658113919198513031005859375
]
},
"b": {
"value": 530.0900000000000318323145620524883270263671875,
"test_run_times": [
9.050000000000000710542735760100185871124267578125
]
}
}
},
"efd4132b4ca34777b8be0494c36cc1edae74ee0d": {
"identifier": "pts\/tensorflow-2.2.0",
"title": "TensorFlow",
"app_version": "2.16.1",
"arguments": "--device cpu --batch_size=1 --model=googlenet",
"description": "Device: CPU - Batch Size: 1 - Model: GoogLeNet",
"scale": "images\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 35.280000000000001136868377216160297393798828125,
"test_run_times": [
6.62000000000000010658141036401502788066864013671875
]
},
"b": {
"value": 37.82000000000000028421709430404007434844970703125,
"test_run_times": [
6.4199999999999999289457264239899814128875732421875
]
}
}
}
}
}