Exploring AMD’s Ambitious ROCm Initiative

Conclusion

AMD’s ROCm platform is a bold step toward portability and heterogeneous computing in the HPC space. AMD’s GPU product line now has an equivalent to the benefits available with NVIDIA’s GPUs through the CUDA framework, but ROCm goes a step further by creating a complete language- and hardware-independent path for GPU-accelerated programming. A developer can write the code once and then compile it for either the CUDA/NVIDIA or the ROCm/AMD environment. Upstream Support for ROCm-enabled GPUs in machine-learning frameworks like TensorFlow and PyTorch/Caffe2 ensures immediate relevance for projects that depend on these tools.

AMD’s vision for a GPU-based, all-open software programming stack is disrupting the whole HPC industry. The open and modular architecture means other vendors can integrate their own technologies into the ROCm stack, and the easy path for porting existing languages and frameworks to ROCm’s neutral format will simplify the learning curve for programmers who want to stay within their preferred coding environment.

Resources

ROCm:

[1] [rocm.github.io]

[2] [amd.com/ROCm]

[3] ROCm documentation: [http://rocm‑documentation.readthedocs.io/]

[4] HIP: [https://github.com/ROCm‑Developer‑Tools/HIP]

HPC:

[5] [amd.com/ROCm/HPC]

[6] [amd.com/HPC]

Machine Learning:

[7] [amd.com/ROCm/ML]

[8] MIOpen: [https://rocmsoftwareplatform.github.o/MIOpen/doc/html/index.html]