- Rocm vs opencl benchmark install#
- Rocm vs opencl benchmark drivers#
- Rocm vs opencl benchmark driver#
- Rocm vs opencl benchmark software#
And it’s all open.ĪM: The HPC space has a big focus on machine learning and AI. That’s the direction we’re headed: making everything composable.
Rocm vs opencl benchmark software#
There are two pieces to ROCm: the core driver, and that’s becoming more like an OS service, and then you have the programming stack, and that’s more like it is with in an operating system, where you can add in modules and composable software like you have in Unix.
All our compiler technologies sit on LLVM, and LLVM actually generates native ISA, and we upstream all that, so there’s a standardized LLVM compiler for the platform. We have an assembler/disassembler as well, which you can use to work on performance-tuning your application. The other thing is, ROCm supports inline assembly, so you can performance-tune the hot loops just like you do on a CPU. We’re doing the same thing with a set of lab operators, which are like directives for GPU computing, but you write your code more like how you historically did – very similar to how you do it in Fortran or C++, so it’s more natural. GS: OpenMP has something very similar – you basically tell it when you want to execute against the GPU. We supply the standard set of languages, and yes we do support OpenCL.ĪM: So the programmer gets to work in a familiar language and still benefit from GPU acceleration? So now, you can dynamically load a set of languages that you want to use on the platform and then build up the userland from there.
Rocm vs opencl benchmark driver#
So, what we wanted to do is make sure we have a foundation at the core to allow us to adapt different languages, so we put in things like standardized loader interfaces, standardized APIs, a system run-time interface, which will actually make the driver act more like an OS service. GS: OpenCL is a solid solution it solves a set of critical needs, but it’s basically only C99, and you know that doesn’t work in the enterprise space. I brought along that Linux sysop sensibility when I joined the ROCm project.ĪM: Isn’t OpenCL an open source solution that supports GPU acceleration? I used to run big clusters and storage arrays. I’ve been working with Linux for a long time.
Rocm vs opencl benchmark install#
To install on Ubuntu, you just add the repo, and then it’s apt-get install rocm, and you’re ready to go.
Rocm vs opencl benchmark drivers#
Historically many drivers are installed with shell scripts, but we wanted closer integration with Linux, so we are actually working with conventional package installers. We wanted to make the system as simple as possible to install.
HCC is a C++ compiler single source that essentially lets you integrate the CPU code and the GPU code into one file. We also built a solution for C++ programmers we call HCC. So, CUDA programmers have a comfortable environment to be in, and they can bring their code across to HIP using our porting tools. Code written in CUDA can port easily to the vendor-neutral HIP format, and from there, you can compile the code for either the CUDA or the ROCm platform. ROCm is open source, so any vendor can work with it and port it to their platform. As you might know, CUDA is GPU aware, but it only supports the GPUs of one vendor. We even have this thing called HIP, which provides an easy way to port code from CUDA. ROCm offers several different languages and paths to code for the GPU. The application work that we do we actually deliver in source form, and we use GitHub to deliver it. There are other GPU-accelerated platforms, of course what’s different about ROCm is, we didn’t stop at the base driver but actually opened up all the tooling and libraries on top of it. Greg Stoner: ROCm is an open source, HPC-class platform for GPU-based computing that is language independent. What is it and why should the world be excited? We sat down with ROCm Senior Director Greg Stoner to find out why ROCm could bring big changes to the HPC space.ĪDMIN Magazine: How about if you start with a brief introduction to ROCm. The ambitious ROCm project builds a complete open source ecosystem around the once-very-proprietary world of GPU-accelerated high-performance computing. AMD released the Radeon Open Compute Ecosystem (ROCm) for GPU-based parallel computing about a year ago.
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