NVIDIA DGX-1 Community-Based Benchmark
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Transcript of NVIDIA DGX-1 Community-Based Benchmark
![Page 1: NVIDIA DGX-1 Community-Based Benchmark](https://reader031.fdocuments.us/reader031/viewer/2022021813/58cfa7661a28ab6b088b5753/html5/thumbnails/1.jpg)
NVIDIA DGX-1 SupercomputerCommunity-Based Deep Learning Benchmark
![Page 2: NVIDIA DGX-1 Community-Based Benchmark](https://reader031.fdocuments.us/reader031/viewer/2022021813/58cfa7661a28ab6b088b5753/html5/thumbnails/2.jpg)
Community-Based Deep Learning Benchmark
We have an NVIDIA DGX-1 available for testingand would like to organise a Community-Driven Benchmark
We plan to have the benchmark set-up by mid-March 2017.If you are interested in running your tests, contact us asap
Please check our Blogpost for info:bit.ly/DGX1-Benchmark
IMPORTANT:
![Page 3: NVIDIA DGX-1 Community-Based Benchmark](https://reader031.fdocuments.us/reader031/viewer/2022021813/58cfa7661a28ab6b088b5753/html5/thumbnails/3.jpg)
Benchmark we’ve already done onNVIDIA GTX1080 - TITAN X Maxwell - TITAN X Pascal - K40
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![Page 4: NVIDIA DGX-1 Community-Based Benchmark](https://reader031.fdocuments.us/reader031/viewer/2022021813/58cfa7661a28ab6b088b5753/html5/thumbnails/4.jpg)
GPU vs Framework vs Network - K40This Benchmark compares the efficiency of various GPUs when training different networks using different frameworks.
This is a common approach that allows us to decide on which framework to use for a given GPU and a given architecture
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![Page 5: NVIDIA DGX-1 Community-Based Benchmark](https://reader031.fdocuments.us/reader031/viewer/2022021813/58cfa7661a28ab6b088b5753/html5/thumbnails/5.jpg)
GPU vs Framework vs Network - TITAN X MaxwellThis Benchmark compares the efficiency of various GPUs when training different networks using different frameworks.
This is a common approach that allows us to decide on which framework to use for a given GPU and a given architecture
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![Page 6: NVIDIA DGX-1 Community-Based Benchmark](https://reader031.fdocuments.us/reader031/viewer/2022021813/58cfa7661a28ab6b088b5753/html5/thumbnails/6.jpg)
GPU vs Framework vs Network - GTX 1080This Benchmark compares the efficiency of various GPUs when training different networks using different frameworks.
This is a common approach that allows us to decide on which framework to use for a given GPU and a given architecture
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![Page 7: NVIDIA DGX-1 Community-Based Benchmark](https://reader031.fdocuments.us/reader031/viewer/2022021813/58cfa7661a28ab6b088b5753/html5/thumbnails/7.jpg)
GPU vs Framework vs Network - TITAN X PascalThis Benchmark compares the efficiency of various GPUs when training different networks using different frameworks.
This is a common approach that allows us to decide on which framework to use for a given GPU and a given architecture
Plea
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heck
our
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![Page 8: NVIDIA DGX-1 Community-Based Benchmark](https://reader031.fdocuments.us/reader031/viewer/2022021813/58cfa7661a28ab6b088b5753/html5/thumbnails/8.jpg)
Minibatch Efficiency for TensorFlowThis Benchmark compares the mini-batch efficiency for each GPU when training different architectures.
As a rule of thumb, larger minibatch size means more efficient training, however be prepare for a few surprise
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![Page 9: NVIDIA DGX-1 Community-Based Benchmark](https://reader031.fdocuments.us/reader031/viewer/2022021813/58cfa7661a28ab6b088b5753/html5/thumbnails/9.jpg)
Minibatch Efficiency for TensorFlowThis Benchmark compares the mini-batch efficiency for each GPU when training different architectures.
As a rule of thumb, larger minibatch size means more efficient training, however be prepare for a few surprise
Plea
se c
heck
our
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t for
info
: bit
.ly/D
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![Page 10: NVIDIA DGX-1 Community-Based Benchmark](https://reader031.fdocuments.us/reader031/viewer/2022021813/58cfa7661a28ab6b088b5753/html5/thumbnails/10.jpg)
Minibatch Efficiency for TensorFlowThis Benchmark compares the mini-batch efficiency for each GPU when training different architectures.
As a rule of thumb, larger minibatch size means more efficient training, however be prepare for a few surprise
Plea
se c
heck
our
Blo
gpos
t for
info
: bit
.ly/D
GX
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ench
mar
k
![Page 11: NVIDIA DGX-1 Community-Based Benchmark](https://reader031.fdocuments.us/reader031/viewer/2022021813/58cfa7661a28ab6b088b5753/html5/thumbnails/11.jpg)
Minibatch Efficiency for TensorFlowThis Benchmark compares the mini-batch efficiency for each GPU when training different architectures.
As a rule of thumb, larger minibatch size means more efficient training, however be prepare for a few surprise
Plea
se c
heck
our
Blo
gpos
t for
info
: bit
.ly/D
GX
1-B
ench
mar
k
![Page 12: NVIDIA DGX-1 Community-Based Benchmark](https://reader031.fdocuments.us/reader031/viewer/2022021813/58cfa7661a28ab6b088b5753/html5/thumbnails/12.jpg)
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