[ Thanks to Cabal for this link.
]
“If you have a mid-range or high-end video card in your
desktop PC, it probably contains a specialized processor called a
GPU or Graphics Processing Unit. The instruction set and memory
architecture of a GPU are designed to handle the types of
operations needed to display complex graphics at high speed. The
instruction sets typically include instructions for manipulating
points in 2D or 3D space and for performing advanced types of
calculations. The architecture of a GPU is also designed to handle
long streams (usually known as vectors) of points with great
efficiency. This takes the form of a deep pipeline and wide,
high-bandwidth access to memory.“A few years ago advanced developers of numerical and scientific
application started to use GPUs to perform general-purpose
calculations, termed GPGPU, for General-Purpose computing on
Graphics Processing Units. Application development continued to
grow as the demands of many additional applications were met with
advances in GPU technology, including high performance double
precision floating point and ECC memory. However, accessibility to
such high-end technology, particularly on HPC cluster
infrastructure for tightly coupled applications, has been elusive
for many developers. Today we are introducing our latest EC2
instance type (this makes eleven, if you are counting at home)
called the Cluster GPU Instance. Now any AWS user can develop and
run GPGPU on a cost-effective, pay-as-you-go basis.”