66b84b38cf
* - get rid of some copy procedures in mmulHelper ops Signed-off-by: Yurii <iuriish@yahoo.com> * - further work on embedding cuda api for batched gemm (cublasGemmBatchedEx) in our mmulHelper class Signed-off-by: Yurii <iuriish@yahoo.com> * - further work on cuda batched gamm api Signed-off-by: Yurii <iuriish@yahoo.com> * - write own cuda kernel performing batched gemm Signed-off-by: Yurii <iuriish@yahoo.com> * missing include in MmulHelper Signed-off-by: raver119 <raver119@gmail.com> * - forgot to keep in code previous correct kernels for mmulNxN, since it may happen that new onw will fail for some reason in future Signed-off-by: Yurii <iuriish@yahoo.com> * disable old tensordot Signed-off-by: raver119 <raver119@gmail.com> * - rewrite cuda kernels for usualGemm and usualGemv Signed-off-by: Yurii <iuriish@yahoo.com> * - profiling mmul helpers Signed-off-by: Yurii <iuriish@yahoo.com> * - prints to check shapes were added Signed-off-by: Yurii <iuriish@yahoo.com> * - correct type of output array Cin mmulNxN Signed-off-by: Yurii <iuriish@yahoo.com> * - take into account possible nans in C array Signed-off-by: Yurii <iuriish@yahoo.com> * slightly change numThreads message Signed-off-by: raver119 <raver119@gmail.com> * - make corrections in accordance to given notes in pr review Signed-off-by: Yurii <iuriish@yahoo.com> |
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|---|---|---|
| .github | ||
| arbiter | ||
| datavec | ||
| deeplearning4j | ||
| docs | ||
| gym-java-client | ||
| jumpy | ||
| libnd4j | ||
| nd4j | ||
| nd4s | ||
| pydatavec | ||
| pydl4j | ||
| rl4j | ||
| scalnet | ||
| .gitignore | ||
| CONTRIBUTING.md | ||
| Jenkinsfile | ||
| LICENSE | ||
| README.md | ||
| change-cuda-versions.sh | ||
| change-scala-versions.sh | ||
| perform-release.sh | ||
| pom.xml | ||
README.md
Monorepo of Deeplearning4j
Welcome to the new monorepo of Deeplearning4j that contains the source code for all the following projects, in addition to the original repository of Deeplearning4j moved to deeplearning4j:
- https://github.com/eclipse/deeplearning4j/tree/master/libnd4j
- https://github.com/eclipse/deeplearning4j/tree/master/nd4j
- https://github.com/eclipse/deeplearning4j/tree/master/datavec
- https://github.com/eclipse/deeplearning4j/tree/master/arbiter
- https://github.com/eclipse/deeplearning4j/tree/master/nd4s
- https://github.com/eclipse/deeplearning4j/tree/master/gym-java-client
- https://github.com/eclipse/deeplearning4j/tree/master/rl4j
- https://github.com/eclipse/deeplearning4j/tree/master/scalnet
- https://github.com/eclipse/deeplearning4j/tree/master/pydl4j
- https://github.com/eclipse/deeplearning4j/tree/master/jumpy
- https://github.com/eclipse/deeplearning4j/tree/master/pydatavec
To build everything, we can use commands like
./change-cuda-versions.sh x.x
./change-scala-versions.sh 2.xx
./change-spark-versions.sh x
mvn clean install -Dmaven.test.skip -Dlibnd4j.cuda=x.x -Dlibnd4j.compute=xx
or
mvn -B -V -U clean install -pl '!jumpy,!pydatavec,!pydl4j' -Dlibnd4j.platform=linux-x86_64 -Dlibnd4j.chip=cuda -Dlibnd4j.cuda=9.2 -Dlibnd4j.compute=<your GPU CC> -Djavacpp.platform=linux-x86_64 -Dmaven.test.skip=true
An example of GPU "CC" or compute capability is 61 for Titan X Pascal.
Want some examples?
We have separate repository with various examples available: https://github.com/eclipse/deeplearning4j-examples
In the examples repo, you'll also find a tutorial series in Zeppelin: https://github.com/eclipse/deeplearning4j-examples/tree/master/tutorials