Numba supports AMD ROC GPU programming by directly compiling a restricted subset of Python code into HSA kernels and device functions following the HSA execution model. Kernels written in Numba appear to have direct access to NumPy arrays.
Several important terms in the topic of HSA programming are listed here:
This document describes the requirements for using ROC. Essentially an AMD dGPU is needed (Fiji, Polaris and Vega families) and a CPU which supports PCIe Gen3 and PCIe Atomics (AMD Ryzen and EPYC, and Intel CPUs >= Haswell), full details are in the linked document. Further a linux operating system is needed, those supported and tested are also listed in the linked document.
Follow this document for installation instructions to enable ROC support for the system. Be sure to use the binary packages for the system’s linux distribution to simplify the process. At this point the install should be tested by running:
$ /opt/rocm/bin/rocminfo
the output of which should list at least two HSA Agents, at least one of which should be a CPU and at least one of which should be a dGPU.
Assuming the installation is working correctly, the ROC support for Numba is
provided by the roctools
package which can be installed via conda
, along
with Numba, from the Numba channel as follows (creating an env called
numba_roc
):
$ conda create -n numba_roc -c numba numba roctools
Activating the env, and then running the Numba diagnostic tool should confirm that Numba is running with ROC support enabled, e.g.:
$ source activate numba_roc
$ numba -s
The output of numba -s
should contain a section similar to:
__ROC Information__
ROC available : True
Available Toolchains : librocmlite library, ROC command line tools
Found 2 HSA Agents:
Agent id : 0
vendor: CPU
name: Intel(R) Core(TM) i7-4790 CPU @ 3.60GHz
type: CPU
Agent id : 1
vendor: AMD
name: gfx803
type: GPU
Found 1 discrete GPU(s) : gfx803
confirming that ROC is available, listing the available toolchains and displaying the HSA Agents and dGPU count.