User Guide

Did you know?
General purpose GPUs are more than just high performance graphics engines. In fact, they do not connect to
computer displays and they do not have video out capabilities, Instead, they perform general purpose
graphical, scientific, and engineering computing and allow the offloading of compute-intensive tasks across all
industries, including life sciences, fluid dynamics, finance, data analytics, atmospheric modeling, as well as
large scale graphic rendering. These types of applications operate on data that is broken down easily into
small chunks that can be operated on in parallel. GPUs are designed for massive parallelism. Whereas a
traditional CPU might have four processing cores, the NVIDIA GPUs have more than 100 times that many
cores (up to 512 cores), providing a peak double-precision capacity of 665 Gigaflops (billions of floating point
operations per second) instead of approximately 50 Gigaflops. The CPU and GPU work together in this
computing model. The main sequential part of the application runs on the CPU, and the computationally-
intensive part runs on the GPU.
IBM BladeCenter GPU Expansion Blade and GPU Expansion Blade II (withdrawn product) 2