AMD Radeon Open Compute Platform hits version 1.3


— 11:43 AM on November 14, 2016

A year ago at the intuitively-named SC15 supercomputing conference, AMD announced its intention to improve its software stack for high-performance computing. The name of that program was the Boltzmann Initiative, and the project's first software fruits came out in April, collectively known as the Radeon Open Compute Platform, or "ROCm." Now, at SC16, AMD is announcing the release of version 1.3 of the platform.

While the red team has been clawing back some gaming market share from the green giants, Nvidia still owns the high-performance compute market. Put simply, ROCm is AMD's answer to Nvidia's CUDA, and aims to assist developers in coding compute-oriented software for Radeon GPUs, along with converting existing CUDA software to run on GCN hardware. At SC16, AMD showed a demo of the CUDA-based Caffe deep-learning framework running on its Radeon GPUs. The company says it was able to translate 99.6% of the code using its HIP tool, and as a result it took less than four days to complete the port. That kind of porting turn-around time could make adopting Radeons a real option for companies that currently rely on CUDA.

The new ROCm version has a lot more than the updated HIP tool, though. Previous versions of ROCm only supported the Hawaii and Fiji GPUs, meaning that ROCm deployments in the field were power-thirsty by nature. ROCm 1.3 now supports the Polaris GPU family, bringing the minimum spec down to the Radeon RX 460. The new version also packs an update to the LLVM-based Heterogeneous Compute Compiler. ROCm software can now be used in virtual environments, too, thanks to new support for Linux KVM GPU pass-through.

Besides announcing the new release, AMD is talking about the future of ROCm at SC16. Software built on the framework currently requires an Intel Haswell or newer CPU, but AMD says future releases will support ARM's AArch64, IBM's Power8, and of course, its own Zen processors. The company also says it plans to rebuild its OpenCL support on top of the ROCm platform to give OpenCL applications "direct-to-metal" access, which might improve their efficiency.

 
   
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