"We introduced an effective algorithm for k-nearest neighbor problem which works on multiple GPUs. By an experiment, we have shown that it runs more than 330 times faster than an implementation on a single core of an up-to-date CPU. We have also shown that the algorithm is effective from the viewpoint of parallelism of GPUs. That is because 1) there is no synchronization between GPUs until the very end of the process and 2) the workload is well balanced."

"Huang at Nvidia has said many times that CUDA is one of the most important advances in computing, and its promise will be evident as programmers learn how to make use of it. Nvidia is already getting lots of its chips designed into supercomputers and servers, thanks to CUDA. And because of CUDA, the 480 chip can do physics processing 2.5 times faster than the previous generation. That means that the environment in a game, such as water in a stream, behaves far more realistically, adding to the overall illusion of a graphics animation. The real question is whether CUDA is really helping or hurting Nvidia’s cause to bring better graphics to the entire world."

"The use of Graphics Processing Units (GPUs) in scientific computing is becoming increasingly common. GPUs are low cost parallel processors that can readily be exploited for many types of general purpose computation. Recently, the computational intelligence community has started to develop for the GPU platform. This web page is primarily dedicated to the use of GPUs as a platform for Genetic Programming. "

"ruby-opengl consists of Ruby extension modules that are bindings for the OpenGL, GLU, and GLUT libraries. It is intended to be a replacement for -- and uses the code from -- Yoshi's ruby-opengl."

"“The opportunity to effectively unlock the capabilities of new generations of programmable compute and graphics processors drove the unprecedented level of cooperation to refine the initial proposal from Apple into the ratified OpenCL 1.0 specification,” said Neil Trevett, chair of the OpenCL working group, president of the Khronos Group and vice president at NVIDIA. “As an open, cross-platform standard, OpenCL is a fundamental technology for next generation software development that will play a central role in the Khronos API ecosystem and we look forward to seeing implementations within the next year.”

"PyGPU is an embedded language in Python, that allow most of Python features (list-comprehensions, higher-order functions, iterators) to be used for constructing GPU algorithms. It uses a image abstraction to abstract away implementation details of the GPU, while still allowing translation to very efficient GPU native-code."