Heterogeneous System Architecture

Heterogeneous System Architecture (HSA) is a cross-vendor set of specifications that allow for the integration of central processing units and graphics processors on the same bus, with shared memory and tasks.[1] The HSA is being developed by the HSA Foundation, which includes (among many others) AMD and ARM. The platform's stated aim is to reduce communication latency between CPUs, GPUs and other compute devices, and make these various devices more compatible from a programmer's perspective,[2]: 3 [3] relieving the programmer of the task of planning the moving of data between devices' disjoint memories (as must currently be done with OpenCL or CUDA).[4]

CUDA and OpenCL as well as most other fairly advanced programming languages can use HSA to increase their execution performance.[5] Heterogeneous computing is widely used in system-on-chip devices such as tablets, smartphones, other mobile devices, and video game consoles.[6] HSA allows programs to use the graphics processor for floating point calculations without separate memory or scheduling.[7]

  1. ^ Tarun Iyer (30 April 2013). "AMD Unveils its Heterogeneous Uniform Memory Access (hUMA) Technology". Tom's Hardware.
  2. ^ George Kyriazis (30 August 2012). Heterogeneous System Architecture: A Technical Review (PDF) (Report). AMD. Archived from the original (PDF) on 28 March 2014. Retrieved 26 May 2014.
  3. ^ "What is Heterogeneous System Architecture (HSA)?". AMD. Archived from the original on 21 June 2014. Retrieved 23 May 2014.
  4. ^ Joel Hruska (26 August 2013). "Setting HSAIL: AMD explains the future of CPU/GPU cooperation". ExtremeTech. Ziff Davis.
  5. ^ Linaro (21 March 2014). "LCE13: Heterogeneous System Architecture (HSA) on ARM". slideshare.net.
  6. ^ "Heterogeneous System Architecture: Purpose and Outlook". gpuscience.com. 9 November 2012. Archived from the original on 1 February 2014. Retrieved 24 May 2014.
  7. ^ "Heterogeneous system architecture: Multicore image processing using a mix of CPU and GPU elements". Embedded Computing Design. Retrieved 23 May 2014.