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ROCm, a New Era in GPU Computing

Welcome to the ROCm Platform

We are excited to present ROCm, the first open-source HPC/Hyperscale-class platform for GPU computing that’s also programming-language independent. We are bringing the UNIX philosophy of choice, minimalism and modular software development to GPU computing. The new ROCm foundation lets you choose or even develop tools and a language run time for your application.

ROCm is built for scale; it supports multi-GPU computing in and out of server-node communication through RDMA. It also simplifies the stack when the driver directly incorporates RDMA peer-sync support.

ROCm has a rich system run time with the critical features that large-scale application, compiler and language-run-time development requires.

HSA Compliant Runtime and Driver for AMD RADEON GPU's

Going to 11: Amping Up the Programming-Language Run-Time Foundation

The ROCr System Runtime is language independent and makes heavy use of the Heterogeneous System Architecture (HSA) Runtime API. This approach provides a rich foundation to exectute programming languages such as HCC C++ and HIP, the Khronos Group’s OpenCL, and Continum’s Anaconda Python.

ROCm_Stack_Diagram

Important features include the following:

  • Multi-GPU coarse-grain shared virtual memory
  • Process concurrency and preemption
  • Large memory allocations
  • HSA signals and atomics
  • User-mode queues and DMA
  • Standardized loader and code-object format
  • Dynamics and offline-compilation support
  • Peer-to-peer multi-GPU operation with RDMA support
  • Profiler trace and event-collection API
  • Systems-management API and tools

Solid Compilation Foundation and Language Support

  • LLVM compiler foundation
  • HCC C++ and HIP for application portability
  • GCN assembler and disassembler

The frontiers of what you can accomplish with ROCm are vast and uncharted. We look forward to working with you to improve the platform so you can use it more effectively in your own projects. Our efforts have opened the door to unique heterogeneous-computing applications that explore what this growing technology can do.