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HDF5 Nvidia GPUDirect Storage VFD

Table of Contents

  1. Description
  2. Installation
  3. Usage and Testing
  4. Known Issues and Limitations
  5. More Information

1. Description

The HDF5 GPUDirect Storage VFD is a Virtual File Driver (VFD) for HDF5 that can be used to interface with Nvidia's GPUDirect Storage (GDS) API. The driver is built as a plugin library that is external to HDF5.

2. Installation

Prerequisites

To build the GDS VFD, the following libraries are required:

  • libhdf5 - The HDF5 library. Minimum version required is 1.14.0. HDF5 must be compiled with support for parallel I/O if building the GDS VFD's tests. Shared libraries must be enabled if loading the GDS VFD as an HDF5 plugin.

  • libcuda - Nvidia CUDA library. Cufile support must also be available.

  • libmpi - MPI library. The GDS VFD's tests use MPI to test functionality of the driver.

Compiled libraries must either exist in the system's library paths or must be pointed to during the GDS VFD build process.

Build instructions

The HDF5 GDS VFD is built using CMake.

CMake

CMake version 2.8.12.2 or greater is required for building the driver.

After obtaining the driver's source code, you can create a build directory within the source tree and run the ccmake or cmake command from it:

cd vfd-gds-X
mkdir build
cd build
ccmake ..

If using ccmake, type 'c' multiple times and choose suitable options or if using cmake, pass these options with -D. Some of these options may be needed if, for example, the required components mentioned previously are not located in default paths.

Setting include directory and library paths may require you to toggle to the advanced mode by typing 't'. Once you are done and do not see any errors, type 'g' to generate makefiles. Once you exit the CMake configuration screen and are ready to build the targets, do:

make

Verbose build output can be generated by appending VERBOSE=1 to the make command.

Assuming that the CMAKE_INSTALL_PREFIX has been set and that you have write permissions to the destination directory, you can install the driver by simply doing:

 make install
CMake options
  • CMAKE_INSTALL_PREFIX - This option controls the install directory that the resulting output files are written to. The default value is /usr/local.
  • CMAKE_BUILD_TYPE - This option controls the type of build used for the VFD. Valid values are Release, Debug, RelWithDebInfo, MinSizeRel; the default build type is RelWithDebInfo.
Driver options
  • BUILD_EXAMPLES - This option is used to enable/disable building of the GDS VFD's HDF5 example programs. The default value is ON.
  • BUILD_TESTING - This option is used to enable/disable building of the GDS VFD's tests. The default value is ON.
  • HDF5_VFD_GDS_CUFILE_DIR - This option controls the directory used when searching for the NVIDIA GPUDirect Storage cuFile library. This option may need to be set if CMake cannot automatically resolve the path.
  • HDF5_VFD_GDS_CUFILE_LIB - This option controls the library used for NVIDIA GPUDirect Storage cuFile support. This option may need to be set if CMake cannot automatically resolve it.
  • HDF5_C_COMPILER_EXECUTABLE - This option controls the HDF5 compiler wrapper script used by the VFD build process. It should be set to the full path to the HDF5 compiler wrapper (usually bin/h5cc), including the name of the wrapper script. The following two options may also need to be set.
  • HDF5_C_LIBRARY_hdf5 - This option controls the HDF5 library used by the VFD build process. It should be set to the full path to the HDF5 library, including the library's name (e.g., /path/libhdf5.so). Used in conjunction with the HDF5_C_INCLUDE_DIR option.
  • HDF5_C_INCLUDE_DIR - This option controls the HDF5 include directory used by the VFD build process. Used in conjunction with the HDF5_C_LIBRARY_hdf5 variable.
  • MPI_C_COMPILER - This option controls the MPI C compiler used by the VFD build process. It should be set to the full path to the MPI C compiler, including the name of the executable.

3. Usage and Testing

To use the HDF5 GDS VFD in an HDF5 application, the driver can either be linked into the application, or it can be dynamically loaded as a plugin. If dynamically loading the GDS VFD, users should ensure that the HDF5_PLUGIN_PATH environment variable points to the directory containing the built VFD library if the VFD has been installed to a non-standard location.

Linked into application

To link the GDS VFD into an HDF5 application, the application should include the H5FDgds.h header that gets installed on the system and should link the installed VFD library (libhdf5_vfd_gds.so, or similar) into the application. Once this has been done, GDS VFD access can be setup by calling H5Pset_fapl_gds(...) on a FAPL within the HDF5 application. Refer to the HDF5 example programs under the examples folder to see how this is done.

Dynamically loaded by FAPL

To explicitly load the GDS VFD inside an HDF5 application, a call to the H5Pset_driver_by_name(...) routine should be made to setup GDS VFD access on a FAPL. This will cause HDF5 to load the VFD as a plugin and set the VFD on the given FAPL. The string "gds" should be given for the driver_name parameter. NULL should be given for the driver_config parameter, as the driver does not currently accept configuration strings.

Dynamically loaded by environment variable

To implicitly load the GDS VFD inside an HDF5 application, the HDF5_DRIVER environment variable may be set to the string "gds". During library initialization, HDF5 will check this environment variable, load the GDS VFD as a plugin and set the VFD as the default file driver on File Access Property Lists. Therefore, any file access that uses H5P_DEFAULT for its FAPL, or which uses a FAPL that hasn't had a specific VFD set on it, will automatically use the GDS VFD for file access.

Usage

Users of the GDS VFD should be aware that using the VFD in a normal, unmodified HDF5 application will cause the VFD to behave similarly to the sec2 VFD; that is, the VFD will make use of POSIX I/O API routines to do file I/O. To make proper use of GPUDirect storage-capable devices with the VFD, the HDF5 application should make use of CUDA memory management API routines (e.g., cudaMalloc) to allocate memory on the device. Then, the device-allocated memory buffer should be passed to H5Dread/H5Dwrite. For examples of this, refer to the HDF5 programs under the examples folder.

4. Known Issues and Limitations

  • For chunked datasets, HDF5 may attempt to cache chunks in its chunk cache under certain circumstances, which can incur overhead when copying between CUDA device memory and host memory. This caching mechanism cannot currently be properly disabled; therefore, performance may suffer for chunked datasets if:
    • filters are applied to the dataset's chunks
    • fill values need to be written to chunks

5. More Information

GPUDirect Storage

HDF5 VFD Plugins RFC