AMD Ryzen 3 3300X 4-Core testing with a MSI B350M GAMING PRO (MS-7A39) v1.0 (2.NR BIOS) and AMD FirePro V3800 512MB 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 2103158-HA-3300XONED31
3300X oneDNN SVT Stuff,
"Sysbench 1.0.20 - Test: CPU",
Higher Results Are Better
"1",8923.79,8916.1,8916.58
"2",8922.35,8915.6,8917.69
"3",8920.07,8920.91,8923.04
"SVT-HEVC 1.5.0 - Tuning: 1 - Input: Bosphorus 1080p",
Higher Results Are Better
"1",4.05,4.03,4.02
"2",4.06,4.03,4.02
"3",4.07,4.03,4.02
"SVT-HEVC 1.5.0 - Tuning: 7 - Input: Bosphorus 1080p",
Higher Results Are Better
"1",62,62,62.07
"2",61.96,61.84,61.94
"3",62.06,61.97,61.74
"SVT-HEVC 1.5.0 - Tuning: 10 - Input: Bosphorus 1080p",
Higher Results Are Better
"1",133.13,133.48,132.95
"2",133.87,132.89,132.36
"3",133.33,133.04,133.24
"SVT-VP9 0.3 - Tuning: VMAF Optimized - Input: Bosphorus 1080p",
Higher Results Are Better
"1",105.86,108.48,109.66
"2",109.23,109.22,110.4
"3",108.89,109.53,108.87
"SVT-VP9 0.3 - Tuning: PSNR/SSIM Optimized - Input: Bosphorus 1080p",
Higher Results Are Better
"1",110.91,110.75,110.34
"2",110.27,110.6,110.83
"3",111.18,111.36,111.22
"SVT-VP9 0.3 - Tuning: Visual Quality Optimized - Input: Bosphorus 1080p",
Higher Results Are Better
"1",87.99,87.65,87.64
"2",88.41,87.84,87.85
"3",87.51,87.83,87.66
"Sysbench 1.0.20 - Test: RAM / Memory",
Higher Results Are Better
"1",16374.76,16461.34,16345.76
"2",16273.07,16372.74,16390.56
"3",16410.29,15644.57,16422.39
"oneDNN 2.1.2 - Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU",
Lower Results Are Better
"1",6.76193,6.78372,6.79588
"2",6.75355,6.75588,6.74346
"3",6.85193,6.7662,6.73987
"oneDNN 2.1.2 - Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU",
Lower Results Are Better
"1",10.4805,10.3461,10.3784
"2",10.5322,10.435,10.4446
"3",10.3294,10.2038,10.1992
"oneDNN 2.1.2 - Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU",
Lower Results Are Better
"1",4.88891,4.88865,4.97503
"2",4.88058,4.88631,4.95856
"3",4.86588,4.89176,4.88581
"oneDNN 2.1.2 - Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU",
Lower Results Are Better
"1",2.73056,2.77777,2.70684
"2",2.69562,2.75027,2.70538
"3",2.66665,2.73182,2.66659
"oneDNN 2.1.2 - Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU",
Lower Results Are Better
"1",21.7895,21.6997,21.7067
"2",21.8744,21.9471,21.8134
"3",21.7935,21.7015,21.7422
"oneDNN 2.1.2 - Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU",
Lower Results Are Better
"1",13.014,12.9729,9.66111,12.9263,12.9331,9.19521,12.8478,9.74981,9.08485,9.13678,9.11502,13.0178,9.25932,12.9886,9.74545
"2",13.0525,12.9539,13.0222
"3",13.0131,13.1754,13.0872
"oneDNN 2.1.2 - Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU",
Lower Results Are Better
"1",11.2597,11.466,11.2687
"2",11.2789,11.4908,11.2717
"3",11.1969,11.281,11.4089
"oneDNN 2.1.2 - Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU",
Lower Results Are Better
"1",22.6448,22.7394,22.5851
"2",22.3397,22.6266,22.6373
"3",22.6542,22.6076,22.5833
"oneDNN 2.1.2 - Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU",
Lower Results Are Better
"1",6.7712,6.82165,6.79889
"2",6.75567,6.8262,6.78362
"3",6.74463,6.78825,6.78038
"oneDNN 2.1.2 - Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU",
Lower Results Are Better
"1",9.08065,9.16806,9.22513
"2",9.13144,9.15789,9.22937
"3",9.25999,9.09671,9.11189
"oneDNN 2.1.2 - Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU",
Lower Results Are Better
"1",5950.38,5997.27,6033.8
"2",5966.51,5982.57,6002.9
"3",5955.11,5982.53,6007.74
"oneDNN 2.1.2 - Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU",
Lower Results Are Better
"1",3099.36,3118.36,3109.93
"2",3124.6,3125.45,3104.55
"3",3122.06,3111.02,3125.11
"oneDNN 2.1.2 - Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU",
Lower Results Are Better
"1",6024.44,6051.86,6020.56
"2",6022.49,6024.32,6028.57
"3",5993.1,6024.51,6008.73
"oneDNN 2.1.2 - Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU",
Lower Results Are Better
"1",3078.76,3113.28,3113.78
"2",3107.2,3104.8,3111.88
"3",3096.2,3116.11,3128.26
"oneDNN 2.1.2 - Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU",
Lower Results Are Better
"1",5.0426,5.00626,5.03596
"2",5.05105,5.00138,5.04777
"3",5.02653,4.99809,5.02498
"oneDNN 2.1.2 - Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU",
Lower Results Are Better
"1",6025.83,6035.16,6029.94
"2",6000.78,6005.42,6024.49
"3",5987.84,6046.77,6013.31
"oneDNN 2.1.2 - Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU",
Lower Results Are Better
"1",3104.72,3118.44,3118.64
"2",3106.4,3108.48,3115.79
"3",3114.8,3090.9,3101.65
"oneDNN 2.1.2 - Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU",
Lower Results Are Better
"1",6.14102,6.0692,6.08645
"2",6.06854,6.13181,6.14827
"3",6.1519,6.07359,6.13874