AMD Ryzen 7 3700X 8-Core testing with a Gigabyte A320M-S2H-CF (F52a BIOS) and HIS AMD Radeon HD 7750/8740 / R7 250E 1GB on Ubuntu 20.04 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 2009023-FI-3700X498660
{
"title": "3700X",
"last_modified": "2020-09-02 13:15:13",
"description": "AMD Ryzen 7 3700X 8-Core testing with a Gigabyte A320M-S2H-CF (F52a BIOS) and HIS AMD Radeon HD 7750\/8740 \/ R7 250E 1GB on Ubuntu 20.04 via the Phoronix Test Suite.",
"systems": {
"R1": {
"identifier": "R1",
"hardware": {
"Processor": "AMD Ryzen 7 3700X 8-Core @ 3.60GHz (8 Cores \/ 16 Threads)",
"Motherboard": "Gigabyte A320M-S2H-CF (F52a BIOS)",
"Chipset": "AMD Starship\/Matisse",
"Memory": "8GB",
"Disk": "240GB TOSHIBA RC100",
"Graphics": "HIS AMD Radeon HD 7750\/8740 \/ R7 250E 1GB",
"Audio": "AMD Oland\/Hainan\/Cape",
"Monitor": "VA2431",
"Network": "Realtek RTL8111\/8168\/8411"
},
"software": {
"OS": "Ubuntu 20.04",
"Kernel": "5.9.0-050900rc1daily20200817-generic (x86_64) 20200816",
"Desktop": "GNOME Shell 3.36.4",
"Display Server": "X Server 1.20.8",
"Display Driver": "modesetting 1.20.8",
"OpenGL": "4.5 Mesa 20.0.8 (LLVM 10.0.0)",
"Compiler": "GCC 9.3.0",
"File-System": "ext4",
"Screen Resolution": "1920x1080"
},
"user": "phoronix",
"timestamp": "2020-09-02 09:50:24",
"data": {
"cpu-scaling-governor": "acpi-cpufreq ondemand",
"cpu-microcode": "0x8701021",
"security": "itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl and seccomp + spectre_v1: Mitigation of usercopy\/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Full AMD retpoline IBPB: conditional STIBP: conditional RSB filling + srbds: Not affected + tsx_async_abort: Not affected"
}
},
"R2": {
"identifier": "R2",
"hardware": {
"Processor": "AMD Ryzen 7 3700X 8-Core @ 3.60GHz (8 Cores \/ 16 Threads)",
"Motherboard": "Gigabyte A320M-S2H-CF (F52a BIOS)",
"Chipset": "AMD Starship\/Matisse",
"Memory": "8GB",
"Disk": "240GB TOSHIBA RC100",
"Graphics": "HIS AMD Radeon HD 7750\/8740 \/ R7 250E 1GB",
"Audio": "AMD Oland\/Hainan\/Cape",
"Monitor": "VA2431",
"Network": "Realtek RTL8111\/8168\/8411"
},
"software": {
"OS": "Ubuntu 20.04",
"Kernel": "5.9.0-050900rc1daily20200817-generic (x86_64) 20200816",
"Desktop": "GNOME Shell 3.36.4",
"Display Server": "X Server 1.20.8",
"Display Driver": "modesetting 1.20.8",
"OpenGL": "4.5 Mesa 20.0.8 (LLVM 10.0.0)",
"Compiler": "GCC 9.3.0",
"File-System": "ext4",
"Screen Resolution": "1920x1080"
},
"user": "phoronix",
"timestamp": "2020-09-02 10:39:19",
"data": {
"cpu-scaling-governor": "acpi-cpufreq ondemand",
"cpu-microcode": "0x8701021",
"security": "itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl and seccomp + spectre_v1: Mitigation of usercopy\/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Full AMD retpoline IBPB: conditional STIBP: conditional RSB filling + srbds: Not affected + tsx_async_abort: Not affected"
}
},
"R3": {
"identifier": "R3",
"hardware": {
"Processor": "AMD Ryzen 7 3700X 8-Core @ 3.60GHz (8 Cores \/ 16 Threads)",
"Motherboard": "Gigabyte A320M-S2H-CF (F52a BIOS)",
"Chipset": "AMD Starship\/Matisse",
"Memory": "8GB",
"Disk": "240GB TOSHIBA RC100",
"Graphics": "HIS AMD Radeon HD 7750\/8740 \/ R7 250E 1GB",
"Audio": "AMD Oland\/Hainan\/Cape",
"Monitor": "VA2431",
"Network": "Realtek RTL8111\/8168\/8411"
},
"software": {
"OS": "Ubuntu 20.04",
"Kernel": "5.9.0-050900rc1daily20200817-generic (x86_64) 20200816",
"Desktop": "GNOME Shell 3.36.4",
"Display Server": "X Server 1.20.8",
"Display Driver": "modesetting 1.20.8",
"OpenGL": "4.5 Mesa 20.0.8 (LLVM 10.0.0)",
"Compiler": "GCC 9.3.0",
"File-System": "ext4",
"Screen Resolution": "1920x1080"
},
"user": "phoronix",
"timestamp": "2020-09-02 12:31:20",
"data": {
"cpu-scaling-governor": "acpi-cpufreq ondemand",
"cpu-microcode": "0x8701021",
"security": "itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl and seccomp + spectre_v1: Mitigation of usercopy\/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Full AMD retpoline IBPB: conditional STIBP: conditional RSB filling + srbds: Not affected + tsx_async_abort: Not affected"
}
}
},
"results": {
"f0551be1b7bac9af382e7b7aa818d1816c616fe6": {
"identifier": "pts\/namd-1.2.1",
"title": "NAMD",
"app_version": "2.14",
"description": "ATPase Simulation - 327,506 Atoms",
"scale": "days\/ns",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"R1": {
"value": 2.26358000000000014750867194379679858684539794921875,
"raw_values": [
2.251510000000000122355459097889252007007598876953125,
2.266550000000000064659388954169116914272308349609375,
2.27268999999999987693399816635064780712127685546875
],
"test_run_times": [
141.530000000000001136868377216160297393798828125,
103.81000000000000227373675443232059478759765625,
103.9500000000000028421709430404007434844970703125
]
},
"R2": {
"value": 2.2605599999999999027977537480182945728302001953125,
"raw_values": [
2.249680000000000124060761663713492453098297119140625,
2.261629999999999807158701514708809554576873779296875,
2.270379999999999842685838302713818848133087158203125
],
"test_run_times": [
102.400000000000005684341886080801486968994140625,
103.349999999999994315658113919198513031005859375,
104
]
},
"R3": {
"value": 2.25710999999999994969357430818490684032440185546875,
"raw_values": [
2.243040000000000144808609547908417880535125732421875,
2.257190000000000029700686354772187769412994384765625,
2.27111000000000018417267710901796817779541015625
],
"test_run_times": [
102.18000000000000682121026329696178436279296875,
103.3299999999999982946974341757595539093017578125,
103.969999999999998863131622783839702606201171875
]
}
}
},
"cd3416e44240b77943cbb384c7ea44c2a9614cb4": {
"identifier": "pts\/tensorflow-lite-1.0.0",
"title": "TensorFlow Lite",
"app_version": "2020-08-23",
"arguments": "--graph=squeezenet.tflite",
"description": "Model: SqueezeNet",
"scale": "Microseconds",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"R1": {
"value": 190706,
"raw_values": [
190535,
190724,
190860
],
"test_run_times": [
60.6400000000000005684341886080801486968994140625,
60.7000000000000028421709430404007434844970703125,
60.75
]
},
"R2": {
"value": 190663,
"raw_values": [
190513,
190658,
190819
],
"test_run_times": [
60.6400000000000005684341886080801486968994140625,
60.67999999999999971578290569595992565155029296875,
60.72999999999999687361196265555918216705322265625
]
},
"R3": {
"value": 190562,
"raw_values": [
190301,
190614,
190772
],
"test_run_times": [
60.75999999999999801048033987171947956085205078125,
60.6700000000000017053025658242404460906982421875,
60.719999999999998863131622783839702606201171875
]
}
}
},
"c54f0992c37a5943d696b0042b8e19e02c23c54d": {
"identifier": "pts\/tensorflow-lite-1.0.0",
"title": "TensorFlow Lite",
"app_version": "2020-08-23",
"arguments": "--graph=inception_v4.tflite",
"description": "Model: Inception V4",
"scale": "Microseconds",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"R1": {
"value": 2758073,
"raw_values": [
2749970,
2763440,
2760810
],
"test_run_times": [
140.280000000000001136868377216160297393798828125,
140.969999999999998863131622783839702606201171875,
140.840000000000003410605131648480892181396484375
]
},
"R2": {
"value": 2756027,
"raw_values": [
2751290,
2757190,
2759600
],
"test_run_times": [
140.340000000000003410605131648480892181396484375,
140.669999999999987494447850622236728668212890625,
140.780000000000001136868377216160297393798828125
]
},
"R3": {
"value": 2757703,
"raw_values": [
2752060,
2756270,
2764780
],
"test_run_times": [
140.3899999999999863575794734060764312744140625,
140.6200000000000045474735088646411895751953125,
141.039999999999992041921359486877918243408203125
]
}
}
},
"4e47784b678508ad5f522adb3d9437ebf2d2dc4f": {
"identifier": "pts\/tensorflow-lite-1.0.0",
"title": "TensorFlow Lite",
"app_version": "2020-08-23",
"arguments": "--graph=nasnet_mobile.tflite",
"description": "Model: NASNet Mobile",
"scale": "Microseconds",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"R1": {
"value": 166065,
"raw_values": [
164847,
166643,
166705
],
"test_run_times": [
60.5499999999999971578290569595992565155029296875,
60.53999999999999914734871708787977695465087890625,
60.60000000000000142108547152020037174224853515625
]
},
"R2": {
"value": 167203,
"raw_values": [
165218,
171410,
164982
],
"test_run_times": [
60.68999999999999772626324556767940521240234375,
60.57000000000000028421709430404007434844970703125,
60.60000000000000142108547152020037174224853515625
]
},
"R3": {
"value": 166611,
"raw_values": [
168761,
166671,
164402
],
"test_run_times": [
60.63000000000000255795384873636066913604736328125,
60.56000000000000227373675443232059478759765625,
60.56000000000000227373675443232059478759765625
]
}
}
},
"ff14b6016c9fc696e403f9e532362c01e6564fb7": {
"identifier": "pts\/tensorflow-lite-1.0.0",
"title": "TensorFlow Lite",
"app_version": "2020-08-23",
"arguments": "--graph=mobilenet_v1_1.0_224.tflite",
"description": "Model: Mobilenet Float",
"scale": "Microseconds",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"R1": {
"value": 128235,
"raw_values": [
128127,
128254,
128324
],
"test_run_times": [
60.64999999999999857891452847979962825775146484375,
60.5799999999999982946974341757595539093017578125,
60.61999999999999744204615126363933086395263671875
]
},
"R2": {
"value": 128066,
"raw_values": [
127844,
128119,
128235
],
"test_run_times": [
60.6400000000000005684341886080801486968994140625,
60.64999999999999857891452847979962825775146484375,
60.57000000000000028421709430404007434844970703125
]
},
"R3": {
"value": 128128,
"raw_values": [
127903,
128260,
128221
],
"test_run_times": [
60.5499999999999971578290569595992565155029296875,
60.590000000000003410605131648480892181396484375,
60.57000000000000028421709430404007434844970703125
]
}
}
},
"7471926c423ed1e3c36c3d5ab372003c88873f4a": {
"identifier": "pts\/tensorflow-lite-1.0.0",
"title": "TensorFlow Lite",
"app_version": "2020-08-23",
"arguments": "--graph=mobilenet_v1_1.0_224_quant.tflite",
"description": "Model: Mobilenet Quant",
"scale": "Microseconds",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"R1": {
"value": 131051,
"raw_values": [
130934,
131097,
131123
],
"test_run_times": [
60.659999999999996589394868351519107818603515625,
60.6099999999999994315658113919198513031005859375,
60.61999999999999744204615126363933086395263671875
]
},
"R2": {
"value": 130967,
"raw_values": [
130844,
131008,
131048
],
"test_run_times": [
60.61999999999999744204615126363933086395263671875,
60.57000000000000028421709430404007434844970703125,
60.5799999999999982946974341757595539093017578125
]
},
"R3": {
"value": 131012,
"raw_values": [
131011,
131031,
130995
],
"test_run_times": [
60.56000000000000227373675443232059478759765625,
60.5799999999999982946974341757595539093017578125,
60.68999999999999772626324556767940521240234375
]
}
}
},
"fd1c35dce606e4556e6c75611dc03b6045835336": {
"identifier": "pts\/tensorflow-lite-1.0.0",
"title": "TensorFlow Lite",
"app_version": "2020-08-23",
"arguments": "--graph=inception_resnet_v2.tflite",
"description": "Model: Inception ResNet V2",
"scale": "Microseconds",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"R1": {
"value": 2499163,
"raw_values": [
2496790,
2500300,
2500400
],
"test_run_times": [
127.3700000000000045474735088646411895751953125,
127.56000000000000227373675443232059478759765625,
127.56000000000000227373675443232059478759765625
]
},
"R2": {
"value": 2496837,
"raw_values": [
2492220,
2497780,
2500510
],
"test_run_times": [
127.1299999999999954525264911353588104248046875,
127.43000000000000682121026329696178436279296875,
127.56999999999999317878973670303821563720703125
]
},
"R3": {
"value": 2496437,
"raw_values": [
2492320,
2497610,
2499380
],
"test_run_times": [
127.1400000000000005684341886080801486968994140625,
127.4200000000000017053025658242404460906982421875,
127.5100000000000051159076974727213382720947265625
]
}
}
}
}
}