|
Apr 2018
|
ResNet50
Google Cloud TPU
source
|
8:52:33
|
$58.53 |
93.11% |
GCP n1-standard-2, Cloud TPU |
TensorFlow v1.8rc1 |
|
Apr 2018
|
ResNet50
Intel(R) Corporation
source
|
3:25:55
|
N/A |
93.02% |
128 nodes with Xeon Platinum 8124M / 144 GB / 36 Cores (Amazon EC2 [c5.18xlarge]) |
Intel(R) Optimized Caffe |
|
Apr 2018
|
AmoebaNet-D N6F256
Google
source
|
1:58:24
|
N/A |
93.17% |
1/16 of a TPUv2 Pod |
TensorFlow 1.8.0-rc1 |
|
Sep 2018
|
ResNet50
Google Cloud TPU
source
|
2:44:31
|
$12.60 |
93.34% |
GCP n1-standard-2, Cloud TPU |
TensorFlow v1.11.0 |
|
Oct 2017
|
ResNet152
Stanford DAWN
source
|
10 days, 3:59:59
|
$1112.64 |
93.00% |
8 K80 / 488 GB / 32 CPU (Amazon EC2 [p2.8xlarge]) |
MXNet 0.11.0 |
|
Apr 2018
|
AmoebaNet-D N6F256
Google Cloud TPU
source
|
7:28:30
|
$49.30 |
93.11% |
GCP n1-standard-2, Cloud TPU |
TensorFlow 1.8.0-rc0 |
|
Mar 2020
|
ResNet50-v1.5
Apsara AI Acceleration(AIACC) team in Alibaba Cloud
source
|
0:21:38
|
$7.43 |
93.05% |
1 ecs.gn6e-c12g1.24xlarge (AlibabaCloud) |
AIACC-Training 1.3 + Tensorflow 2.1 |
|
May 2019
|
ResNet-50
ModelArts Service of Huawei Cloud
source
|
0:02:43
|
N/A |
93.10% |
16 nodes with InfiniBand (8*V100 with NVLink for each node) |
Moxing v1.13.0 + TensorFlow v1.13.1 |
|
Apr 2018
|
ResNet56
Intel(R) Corporation
source
|
3:31:47
|
N/A |
93.11% |
128 nodes with Xeon Platinum 8124M / 144 GB / 36 Cores (Amazon EC2 [c5.18xlarge]) |
Intel(R) Optimized Caffe |
|
Aug 2019
|
Resnet 50
ZTE AI Platform
source
|
0:23:11
|
N/A |
93.03% |
8 nodes with InfiniBand (8*P100 for each node) |
TensorFlow v1.12.0 |
|
Apr 2019
|
ResNet50
Setu Chokshi (MS AI MVP | PropertyGuru)
source
|
1:42:23
|
$20.89 |
93.02% |
Azure ND40s_v2 |
PyTorch 1.0 |
|
Sep 2018
|
Resnet 50
Andrew Shaw, Yaroslav Bulatov, Jeremy Howard
source
|
0:29:43
|
$48.48 |
93.02% |
32 * V100 (4 machines - AWS p3.16xlarge) |
ncluster / Pytorch 0.5.0a0+0e8088d |
|
Oct 2017
|
ResNet152
Stanford DAWN
source
|
13 days, 10:41:37
|
$2323.39 |
93.38% |
4 M60 / 488 GB / 64 CPU (Amazon EC2 [g3.16xlarge]) |
TensorFlow v1.3 |
|
Apr 2018
|
ResNet50
Intel(R) Corporation
source
|
6:09:50
|
N/A |
93.05% |
64 nodes with Xeon Platinum 8124M / 144 GB / 36 Cores (Amazon EC2 [c5.18xlarge]) |
Intel(R) Optimized Caffe |
|
Mar 2020
|
ResNet50-v1.5
Apsara AI Acceleration(AIACC) team in Alibaba Cloud
source
|
0:02:38
|
$14.42 |
93.04% |
16 ecs.gn6e-c12g1.24xlarge (AlibabaCloud) |
AIACC-Training 1.3 + Tensorflow 2.1 |
|
Apr 2018
|
AmoebaNet-D N6F256
Google
source
|
1:06:32
|
N/A |
93.03% |
1/4 of a TPUv2 Pod |
TensorFlow 1.8.0-rc1 |
|
Aug 2019
|
Resnet 50
Chuan Li
source
|
12:39:49
|
$19.00 |
93.05% |
Lambda GPU Cloud - 4x GTX 1080 Ti |
ncluster / Pytorch 1.0.0 |
|
Sep 2018
|
Resnet 50
Andrew Shaw, Yaroslav Bulatov, Jeremy Howard
source
|
0:18:53
|
$61.63 |
93.19% |
64 * V100 (8 machines - AWS p3.16xlarge) |
ncluster / Pytorch 0.5.0a0+0e8088d |
|
Feb 2019
|
Resnet 50 v1
GE Healthcare (Min Zhang)
source
|
1:44:34
|
$42.66 |
93.24% |
8*V100 (single p3.16xlarge) |
tensorflow 1.11 + horovod |
|
Sep 2018
|
ResNet-50
fast.ai/DIUx (Yaroslav Bulatov, Andrew Shaw, Jeremy Howard)
source
|
0:18:06
|
$118.07 |
93.11% |
16 p3.16xlarge (AWS) |
PyTorch 0.4.1 |
|
Apr 2018
|
ResNet50
Google
source
|
0:30:43
|
N/A |
93.03% |
Half of a TPUv2 Pod |
TensorFlow 1.8.0-rc1 |
|
Dec 2017
|
ResNet152
ppwwyyxx
source
|
1 day, 20:28:27
|
N/A |
93.94% |
8 P100 / 512 GB / 40 CPU (NVIDIA DGX-1) |
tensorpack 0.8.0 |
|
Apr 2018
|
Resnet 50
fast.ai + students team: Jeremy Howard, Andrew Shaw, Brett Koonce, Sylvain Gugger
source
|
2:57:28
|
$72.40 |
93.05% |
8 * V100 (AWS p3.16xlarge) |
fastai / pytorch |
|
Jan 2018
|
ResNet50
DIUX
source
|
14:37:59
|
$358.22 |
93.07% |
p3.16xlarge |
tensorflow 1.5, tensorpack 0.8.1 |
|
Mar 2018
|
ResNet50
Google Cloud TPU
source
|
12:26:39
|
$82.07 |
93.15% |
GCP n1-standard-2, Cloud TPU |
TensorFlow v1.7rc1 |
|
Dec 2018
|
ResNet-50
ModelArts Service of Huawei Cloud
source
|
0:09:22
|
N/A |
93.23% |
16 * 8 * Tesla-V100(ModelArts Service) |
Huawei Optimized MXNet |
|
Sep 2018
|
ResNet50
Google Cloud TPU
source
|
5:52:31
|
$27.00 |
93.36% |
GCP n1-standard-2, Cloud TPU |
TensorFlow v1.11.0 |