Heterogenous Compute
As we reach the end of Moore’s law (CPU performance doubles every 2 years) and Dennard scaling (as transistors get smaller their power density remains constant - so each transistor uses less power), the focus of computer architecture has moved towards Heterogenous computing.
A good overview of computer architecture in general and this topic in particular may be found in:
Computer Architecture: A Quantative Approach (John Hennesy, David Patterson) Amazon
John Hennesy and David Patterson 2017 ACM Turing Award Lecture YouTube video
What is heterogenous compute?
This term is used to cover the mixture of traditional CPU based computing that is meant to do fairly well on most tasks with more special purpose devices that are optimized for particular types of algorithm.
This includes:
CPUs - It may seem obvious but the thing that makes these approaches heterogenous is that we have a mixture of different compute devices. The highest performance systems make use of the CPU for what it is best at in conjunction with more specialist devices.
GPUs - Modern Graphics Processors have features specifically to enable / enhance their use for non graphics, i.e. compute tasks.
DSPs - A class of general purpose CPUs with very different characteristics from a CPU. These are especially suited for stream processing.
FPGAs - Flexible devices that let you implement almost any hardware design you want. This is often the path to a cheap or on demand domain specific accelerator.
Domain Specific Architectures (DSAs) - These can still have a high degree of programability but they are designed to take on one class of problems. GPUs started as domain specific processors but have evolved to handle a wide range of applications, putting them in a class of their own.
This section is not intended to be a complete description of any of these large areas, but rather a brief introduction to point you in the right direction.
System on Chip (SoC)
Mobile processors and increasingly desktop processors are heterogenous devices. An extreme example is the recently announced NVIDIA Xavier SoC
8 Core CPU
8 SM Volta GPU
Deep learning accelerator
Programable vision accelerator (vector processing unit)
Stereo and optic flow engine
Image/signal processor
General Resources
There are some good online resources and conferences with the latest news on hardware accelerators.
Websites
http://www.nextplatform.com : A website focused on HPC and large scale computing. As heteregenous computing forms a large part of high end HPC, this is often a good place to follow upcoming trends.
Conferences
Computer architecture conferences:
http://www.hotchips.com : Mainly industry presentations.
http://www.isca.com : A conference with a more academic focus.