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authorAndrew M. B. Boktor <[email protected]>2012-04-25 12:39:52 -0800
committerAndrew Boktor <[email protected]>2014-08-14 13:19:06 -0700
commit54d72b20add6d79c25d97e4963b5c05bb0759e88 (patch)
treeff72c66580cff5cc4214253fa1c6b0d8a7aab2a9 /README
parentaa6d26d41e88634f0c5143bf87154cef1db06dd7 (diff)
Making it clear that we do not need static linking
[git-p4: depot-paths = "//depot/gpgpu_sim_research/fermi/distribution/": change = 12121]
Diffstat (limited to 'README')
-rw-r--r--README12
1 files changed, 8 insertions, 4 deletions
diff --git a/README b/README
index 5379932..a2c0a15 100644
--- a/README
+++ b/README
@@ -180,11 +180,15 @@ file to "1" (Note: you need CUDA version 4.0 or higher).
Now To run a CUDA application on the simulator, simply execute
source setup_environment <build_type>
-
+
Use the same <build_type> you used while building the simulator. Then just
-launch the executable as you would if it was to run on the hardware. To revert
-back to running on the hardware, remove GPGPU-Sim from your LD_LIBRARY_PATH
-environment variable.
+launch the executable as you would if it was to run on the hardware. By
+running "source setup_environment <build_type>" you change your LD_LIBRARY_PATH
+to point to GPGPU-Sim's instead of CUDA or OpenCL runtime so that you do NOT
+need to re-compile your application simply to run it on GPGPU-Sim.
+
+To revert back to running on the hardware, remove GPGPU-Sim from your
+LD_LIBRARY_PATH environment variable.
Running OpenCL applications is identical to running CUDA applications. However,
OpenCL applications need to communicate with the NVIDIA driver in order to