Accelerator Adoption Will Thrive With Software Standardization
Accelerator technologies are receiving more attention throughout the computing infrastructure, from the endpoint to the data center. User needs, ranging from managing the explosion of data to time-critical business processes, have driven this interest for exponentially greater computation in a slowly growing energy budget.
While the conversation for the past decade focused on the use of programmable graphics accelerators (GPUs), accelerator architectures today are far more diverse. Specialized accelerators for artificial intelligence (AI), high-performance computing (HPC), cryptography, data movement and IO, and telecommunications currently deployed or in development use a diverse set of architectures: superscalar, vector, dataflow/spatial, matrix, as well as emerging neuromorphic and quantum. Beyond architectural diversity, accelerator implementations also vary from the traditional IO connected devices to coherent memory devices to devices tightly integrated into the CPU complex.