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feature/cricketd
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fix no output on weird shells, e.g. ssh
fix using logger function before initialization
cublas: remove usage of new APIs if we compile for CUDA 10
add support for cuModuleLoadData
improve debug output for cuModuleLoad
improve cublas implementation, add cudnnBackend implementation
improve docs/pytorch.md
improve logging for unloading of modules
fix faulty if statement when intercepting dlopen calls
add cublas and cudnn functions to support mnistCUDNN sample
update readme with new server instructions and update pipeline status image
implement three more cudnn tensor APIs
implement cudnn tensor functions
add basic cuBLAS support
add server side cudnn lrn implementations, fix some function names
add cudnn LRN api
add cudnn dependency to Dockerfiles
implement cudaMemset Async APIs
add cudnn activation and pooling apis
add more cuDNN APIs
use resource managers for cudnn api
add cuDNN implementation
add cuDNN API stubs
use fixed size rpc array instead of opaque variable length array for cudaDeviceProp
add cuDNN tests to tests/samples
Start moving gpu-checkpointing to cpu folder.
gpu-development
gpu-development
improve support for cuGetProcAddress
add libgl dependency to pytorch documentation
add v2 implementation of cudaGetDeviceProperties
update docs to not deactivate compression as we now support compressed pytorch kernels
use uint64_t for decompressions to fix overflowing of range and length specifiers for very long compressed segments
fix potential segfault because of missing variadic parameter in logging
fix decompression not working for long uncompressed lz4 segments
fix elf decompression handling padding wrong in some circumstances
add documentation on how to use pytorch to docs/pytorch.md
change c standard to gnu11, improve logging
add cpu-server-nvml head
exclude some nvml definitions when compiling with an old CUDA version to make the CI happy
add nvml library to dockerfiles
add license to pytorch_minimal.py
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