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new 1f0f435 [SYSTEMDS-2970] Guide for running SystemDS with GPU
1f0f435 is described below
commit 1f0f4356ca00970cea1f3093a7be237f4a4bdd3c
Author: Janardhan Pulivarthi <[email protected]>
AuthorDate: Sun May 9 09:40:29 2021 +0530
[SYSTEMDS-2970] Guide for running SystemDS with GPU
* Initial document for gpu usage
* Add hardware requirements
* `cuda` & `cudnn` install instructions
Related discussion:
http://mail-archives.apache.org/mod_mbox/systemds-dev/202105.mbox/%3CCAObMueUEf4JMeuzUhU0G%3DansUFojH6gXGNaxg1t5fwffW6iZRw%40mail.gmail.com%3E
Inspired from:
* https://systemds.apache.org/docs/1.2.0/gpu
* https://www.tensorflow.org/install/gpu
* https://cloud.google.com/compute/docs/gpus/install-drivers-gpu
*
https://www.ibm.com/docs/en/vip/1.4.0?topic=server-installing-nvidia-gpu-packages-ubuntu
Closes #1269
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1 file changed, 122 insertions(+)
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+---
+layout: site
+title: Run SystemDS with GPU
+---
+<!--
+{% comment %}
+Licensed to the Apache Software Foundation (ASF) under one or more
+contributor license agreements. See the NOTICE file distributed with
+this work for additional information regarding copyright ownership.
+The ASF licenses this file to you under the Apache License, Version 2.0
+(the "License"); you may not use this file except in compliance with
+the License. You may obtain a copy of the License at
+
+http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+{% endcomment %}
+-->
+
+This guide covers the GPU hardware and software setup for using SystemDS `gpu`
mode.
+
+- [Requirements](#requirements)
+- [Windows](#windows)
+- [Command-line users](#command-line-users)
+- [Scala Users](#scala-users)
+- [Advanced Configuration](#advanced-configuration)
+ - [Using single precision](#using-single-precision)
+- [Training very deep network](#training-very-deep-network)
+ - [Shadow buffer](#shadow-buffer)
+ - [Unified memory allocator](#unified-memory-allocator)
+
+## Requirements
+
+### Hardware
+
+The following GPUs are supported:
+
+* NVIDIA GPU cards with CUDA architectures 5.0, 6.0, 7.0, 7.5, 8.0 and higher
than 8.0.
+For CUDA enabled gpu cards at [CUDA
GPUs](https://developer.nvidia.com/cuda-gpus)
+* For GPUs with unsupported CUDA architectures, or to avoid JIT compilation
from PTX, or to
+use difference versions of the NVIDIA libraries, build on Linux from source
code.
+* Release artifacts contain PTX code for the latest supported CUDA
architecture.
+
+### Software
+
+The following NVIDIA software is required to be installed in your system:
+
+CUDA toolkit
+
+ 1. [NVIDIA GPU drivers](https://www.nvidia.com/drivers) - CUDA 10.2 requires
>= 440.33 driver. see
+ [CUDA
compatibility](https://docs.nvidia.com/deploy/cuda-compatibility/index.html).
+ 3. [CUDA 10.2](https://developer.nvidia.com/cuda-10.2-download-archive)
+ 4. [CUDNN 7.x](https://developer.nvidia.com/cudnn)
+
+## Windows
+
+Install the hardware and software requirements.
+
+Add CUDA, CUPTI, and cuDNN installation directories to `%PATH%` environmental
+variable. Neural networks won't run without cuDNN `cuDNN64_7*.dll`.
+See [Windows install from source guide](./windows-source-installation.md).
+
+```sh
+SET PATH=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.2\bin;%PATH%
+SET PATH=C:\Program Files\NVIDIA GPU Computing
Toolkit\CUDA\v10.2\extras\CUPTI\lib64;%PATH%
+SET PATH=C:\Program Files\NVIDIA GPU Computing
Toolkit\CUDA\v10.2\include;%PATH%
+SET PATH=C:\tools\cuda\bin;%PATH%
+```
+
+## Command-line users
+
+To enable the GPU backend via command-line, please provide
`systemds-*-extra.jar` in the classpath and `-gpu` flag.
+
+```
+spark-submit --jars systemds-*-extra.jar SystemDS.jar -f myDML.dml -gpu
+```
+
+To skip memory-checking and force all GPU-enabled operations on the GPU,
please provide `force` option to the `-gpu` flag.
+
+```
+spark-submit --jars systemds-*-extra.jar SystemDS.jar -f myDML.dml -gpu force
+```
+
+## Scala users
+
+To enable the GPU backend via command-line, please provide
`systemds-*-extra.jar` in the classpath and use
+the `setGPU(True)` method of MLContext API to enable the GPU usage.
+
+```
+spark-shell --jars systemds-*-extra.jar,SystemDS.jar
+```
+
+## Advanced Configuration
+
+### Using single precision
+
+By default, SystemDS uses double precision to store its matrices in the GPU
memory.
+To use single precision, the user needs to set the configuration property
`sysds.floating.point.precision`
+to `single`. However, with exception of BLAS operations, SystemDS always
performs all CPU operations
+in double precision.
+
+### Training very deep network
+
+#### Shadow buffer
+
+To train very deep network with double precision, no additional configurations
are necessary.
+But to train very deep network with single precision, the user can speed up
the eviction by
+using shadow buffer. The fraction of the driver memory to be allocated to the
shadow buffer can
+be set by using the configuration property
`sysds.gpu.eviction.shadow.bufferSize`.
+In the current version, the shadow buffer is currently not guarded by SystemDS
+and can potentially lead to OOM if the network is deep as well as wide.
+
+#### Unified memory allocator
+
+SystemDS uses CUDA's memory allocator and performs on-demand eviction using
only
+the Least Recently Used (LRU) eviction policy as per
`sysds.gpu.eviction.policy`.
+To use CUDA's unified memory allocator that performs page-level eviction
instead,
+please set the configuration property `sysml.gpu.memory.allocator` to
`unified_memory`.
