3700X

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
Jump To Table - Results

View

Do Not Show Noisy Results
Do Not Show Results With Incomplete Data
Do Not Show Results With Little Change/Spread
List Notable Results

Statistics

Show Overall Harmonic Mean(s)
Show Overall Geometric Mean
Show Wins / Losses Counts (Pie Chart)
Normalize Results
Remove Outliers Before Calculating Averages

Graph Settings

Force Line Graphs Where Applicable
Convert To Scalar Where Applicable
Prefer Vertical Bar Graphs

Multi-Way Comparison

Condense Multi-Option Tests Into Single Result Graphs

Table

Show Detailed System Result Table

Run Management

Highlight
Result
Hide
Result
Result
Identifier
View Logs
Performance Per
Dollar
Date
Run
  Test
  Duration
R1
September 02 2020
  32 Minutes
R2
September 02 2020
  31 Minutes
R3
September 02 2020
  31 Minutes
Invert Hiding All Results Option
  31 Minutes

Only show results where is faster than
Only show results matching title/arguments (delimit multiple options with a comma):
Do not show results matching title/arguments (delimit multiple options with a comma):


{ "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 ] } } } } }