From 71cafe7842e7bb24d75f2db2b7c37b8e7fd8add8 Mon Sep 17 00:00:00 2001 From: Herbert Kruitbosch Date: Thu, 18 Jan 2018 08:43:14 +0000 Subject: [PATCH 1/3] Update 'README.md' --- README.md | 5 +++++ 1 file changed, 5 insertions(+) diff --git a/README.md b/README.md index e69de29..fdaac1d 100644 --- a/README.md +++ b/README.md @@ -0,0 +1,5 @@ +# GPU / CPU Benchmarks for tensorflow and keras + +The first benchmark tests matrix multiplication in tensorflow + +[Matrix multiplication benchmark](01.%20Matrix%20Multiplication.ipynb) \ No newline at end of file From 6d4c981cf9b7fb43e7ed031f03e212f48f88684d Mon Sep 17 00:00:00 2001 From: Herbert Kruitbosch Date: Thu, 18 Jan 2018 08:59:57 +0000 Subject: [PATCH 2/3] Update 'README.md' --- README.md | 25 +++++++++++++++++++++++-- 1 file changed, 23 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index fdaac1d..62b325b 100644 --- a/README.md +++ b/README.md @@ -1,5 +1,26 @@ # GPU / CPU Benchmarks for tensorflow and keras +The benchmarks run on all the devices that tensorflow finds. If that should include a GPU, make sure to install the python egg `tensorflow-gpu`, also make sure the nvidia kernel module has the version supported by your cuda installation, in my case I needed the ubuntu-package `nvidia-384==384.111-0ubuntu1` (the 111-part also has to match). You'll see an error message in the **console** (not the notebook) when importing tensorflow and the versions mismatch. Also make sure cuda is in your `LD_LIBRARY_PATH`, in my case `/usr/local/cuda-8.0/targets/x86_64-linux/lib/` for the ubuntu package `cuda-8.0`, the folder should contain object files like `libcudnn.so` ('updatedb' and `locate libcuda.so` to find such a folder on your linux system). -The first benchmark tests matrix multiplication in tensorflow -[Matrix multiplication benchmark](01.%20Matrix%20Multiplication.ipynb) \ No newline at end of file +Run the benchmarks preferrably in a virtualenv with `python>=3.4,<4` + + virtualenv --python=/usr/bin/python3 gpubenchmark + source gpubenchmark/bin/activate + pip3 install numpy scipy tensorflow-gpu keras jupyter + jupyter-notebook # starts a http-server + +instead of running `jupyter-notebook`, you can also make python-scripts. + +## Experiments + +Benchmark for matrix multiplication in tensorflow + +[Matrix multiplication benchmark](01.%20Matrix%20multiplication.ipynb) + +Benchmark for training and predicting on a 5-layer neural network in keras+tensorflow + +[4-layer Dense Neural Network](02.%20Simple%20Neural%20Network%20training%20+%20evaluation.ipynb) + +Benchmarks for predictions using ResNet50, Inception v3, VGG16 and VGG19 + +[Popular deep learning models](03.%20Popular%20image%20classification%20models.ipynb) \ No newline at end of file From d7b85e03dcbdb50394490a86b0a07fe0a1b290e4 Mon Sep 17 00:00:00 2001 From: Herbert Kruitbosch Date: Thu, 18 Jan 2018 09:01:01 +0000 Subject: [PATCH 3/3] Update 'README.md' --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 62b325b..7322ddb 100644 --- a/README.md +++ b/README.md @@ -1,5 +1,5 @@ # GPU / CPU Benchmarks for tensorflow and keras -The benchmarks run on all the devices that tensorflow finds. If that should include a GPU, make sure to install the python egg `tensorflow-gpu`, also make sure the nvidia kernel module has the version supported by your cuda installation, in my case I needed the ubuntu-package `nvidia-384==384.111-0ubuntu1` (the 111-part also has to match). You'll see an error message in the **console** (not the notebook) when importing tensorflow and the versions mismatch. Also make sure cuda is in your `LD_LIBRARY_PATH`, in my case `/usr/local/cuda-8.0/targets/x86_64-linux/lib/` for the ubuntu package `cuda-8.0`, the folder should contain object files like `libcudnn.so` ('updatedb' and `locate libcuda.so` to find such a folder on your linux system). +The benchmarks run on all the devices that tensorflow finds. If that should include a GPU, make sure to install the python egg `tensorflow-gpu`, also make sure the nvidia kernel module has the version supported by your cuda installation, in my case I needed the ubuntu-package `nvidia-384==384.111-0ubuntu1` (the 111-part also has to match). You'll see an error message in the **console** (not the notebook) when importing tensorflow and the versions mismatch. Also make sure cuda is in your `LD_LIBRARY_PATH`, in my case `/usr/local/cuda-8.0/targets/x86_64-linux/lib/` for the ubuntu package `cuda-8.0`, the folder should contain object files like `libcudnn.so` (`updatedb` and `locate libcuda.so` to find such a folder on your linux system). Run the benchmarks preferrably in a virtualenv with `python>=3.4,<4`