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authorTor Aamodt <[email protected]>2019-05-30 07:49:58 -0700
committerGitHub <[email protected]>2019-05-30 07:49:58 -0700
commit6337105df018f25ad1b58afa040d8b1006f2a0ce (patch)
treefd45030f1adc6b60ca77c7ecd5af89aebb7e1c03
parent5837143ef70e20c362083b36c55e4c473f59f358 (diff)
parent6d99e17334235b9e94abb82b0aee66c78f737748 (diff)
Merge pull request #129 from PSuchita/dev
Updating README
-rw-r--r--README26
1 files changed, 25 insertions, 1 deletions
diff --git a/README b/README
index 998cb51..ff6664f 100644
--- a/README
+++ b/README
@@ -177,7 +177,7 @@ GPGPU-Sim dependencies:
* flex
* zlib
* CUDA Toolkit
-
+
GPGPU-Sim documentation dependencies:
* doxygen
* graphvi
@@ -208,6 +208,9 @@ python-matplotlib"
CUDA SDK dependencies:
"sudo apt-get install libxi-dev libxmu-dev libglut3-dev"
+If you are running applications which use NVIDIA libraries such as cuDNN and
+cuBLAS, install them too.
+
Finally, ensure CUDA_INSTALL_PATH is set to the location where you installed
the CUDA Toolkit (e.g., /usr/local/cuda) and that $CUDA_INSTALL_PATH/bin is in
your PATH. You probably want to modify your .bashrc file to incude the
@@ -216,6 +219,10 @@ following (this assumes the CUDA Toolkit was installed in /usr/local/cuda):
export CUDA_INSTALL_PATH=/usr/local/cuda
export PATH=$CUDA_INSTALL_PATH/bin
+If running applications which use cuDNN or cuBLAS:
+ export CUDNN_PATH=<Path To cuDNN Directory>
+ export LD_LIBRARY_PATH=$CUDA_INSTALL_PATH/lib64:$CUDA_INSTALL_PATH/lib:$CUDNN_PATH/lib64
+
Step 2: Build
=============
@@ -261,6 +268,23 @@ ldd <your_application_name>
You should see that your application is using libcudart.so file in GPGPUSim directory.
+If running applications which use cuDNN or cuBLAS:
+
+ * Modify the Makefile or the compilation command of the application to change
+ all the dynamic links to static ones, for example:
+ * -L$(CUDA_PATH)/lib64 -lcublas to
+ -L$(CUDA_PATH)/lib64 -lcublas_static
+
+ * -L$(CUDNN_PATH)/lib64 -lcudnn to
+ -L$(CUDNN_PATH)/lib64 -lcudnn_static
+
+ * Modify the Makefile or the compilation command such that the following
+ flags are used by the nvcc compiler:
+ -gencode arch=compute_61,code=compute_61
+
+ (the number 61 refers to the SM version. You would need to set it based
+ on the GPGPU-Sim config "-gpgpu ptx force max capability" you use)
+
Copy the contents of configs/QuadroFX5800/ or configs/GTX480/ to your
application's working directory. These files configure the microarchitecture
models to resemble the respective GPGPU architectures.