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Merge pull request #398 from zwets/fix-cudnn-frontend-check

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Fix detection of cudnn-frontend in '.' on Linux
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Andrej 2024-05-10 12:13:53 +02:00 • committed by GitHub
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2 changed files with 5 additions and 7 deletions
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10
Makefile
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@ -19,8 +19,7 @@ NVCC_INCLUDES =
NVCC_LDLIBS =
NCLL_INCUDES =
NVCC_CUDNN =
# overridable flag for multi-GPU training. by default we won't build with cudnn
# because it bloats up the compile time from a few seconds to ~minute
# By default we don't build with cudnn because it blows up compile time from a few seconds to ~minute
USE_CUDNN ?= 0
# Function to check if a file exists in the PATH
@ -86,16 +85,15 @@ else
endif
# Check and include cudnn if available
# You can override the path to cudnn frontend by setting CUDNN_FRONTEND_PATH=your_path on the make command line
# You can override the path to cudnn frontend by setting CUDNN_FRONTEND_PATH on the make command line
# By default, we look for it in HOME/cudnn-frontend/include and ./cudnn-frontend/include
# Refer to the README for cuDNN install instructions
ifeq ($(USE_CUDNN), 1)
ifeq ($(SHELL_UNAME), Linux)
# hard-coded path for now in either . or ($HOME) directory
# this can be overridden by setting CUDNN_FRONTEND_PATH on the command line
ifeq ($(shell [ -d $(HOME)/cudnn-frontend/include ] && echo "exists"), exists)
$(info ✓ cuDNN found, will run with flash-attention)
CUDNN_FRONTEND_PATH ?= $(HOME)/cudnn-frontend/include
else ifeq ($(shell [ -d cudnn-frontend/include ] && echo "exists"),)
else ifeq ($(shell [ -d cudnn-frontend/include ] && echo "exists"), exists)
$(info ✓ cuDNN found, will run with flash-attention)
CUDNN_FRONTEND_PATH ?= cudnn-frontend/include
else

2
README.md
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@ -265,7 +265,7 @@ sudo apt-get update
sudo apt-get -y install libcudnn9-dev-cuda-12
```
On top of this you need the [cuDNN frontend](https://github.com/NVIDIA/cudnn-frontend/tree/main), but this is just header files. So simply download the repo to your disk, currently assumed to be in your home directory (i.e. the Makefile looks for `~/cudnn-frontend/include`).
On top of this you need the [cuDNN frontend](https://github.com/NVIDIA/cudnn-frontend/tree/main), but this is just header files. Simply clone the repo to your disk. The Makefile currently looks for it in either your home directory or the current directory. If you have put it elsewhere, add `CUDNN_FRONTEND_PATH=/path/to/your/cudnn-frontend/include` to the `make` command-line.
**Multi-GPU training**. As of April 26, 2024 there is now also support for multi-GPU training using MPI and NCCL. Make sure you install MPI, e.g. on Linux: