On recent PC graphics cards, fully programmable parallel geometry and pixel units are available providing powerful instruction sets to perform arithmetic and logical operations. In addition to computational functionality, pixel (fragment) units also provide an efficient memory interface to local graphics data. To take full advantage of this technology, considerable effort has been spent on the ...

Krylov subspace iterative solvers are often the method of choice when solving large sparse linear systems. At the same time, hardware accelerators such as graphics processing units continue to offer significant floating point performance gains for matrix and vector computations through easy-to-use libraries of computational kernels. However, as these libraries are usually composed of a well opt...

Graphics processing units have now been used for scientific calculations for over a decade, going from early proof-of-concepts to industrial use today. The inherent reason is that graphics processors are far more powerful than CPUs when it comes to both floating point operations and memory bandwidth, illustrated by the fact that a growing portion of the top 500 supercomputers in the world now u...

Recent technological advances have led to a number of emerging platforms such as multi-cores, reconfigurable computing, and graphics processing units. We present a comparative study of multi-cores, field-programmable gate arrays, and graphics processing units for a Quantum Monte Carlo chemistry application. The speedups of these implementations are measured relative to a multi-core implementati...

Modern graphics cards for computers, and especially their graphics processing units (gpus), are designed for fast rendering of graphics. In order to achieve this gpus have a parallel architecture which can be exploited for general-purpose computing on graphics processing units (gpgpu) as a complement to the central processing unit (cpu). In this paper gpgpu techniques are used to implement stat...