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Lecture Notes in Computer Science
Computing many small 2D convolutions using FFTs is a basis for a large number of applications in many domains in science and engineering, among them electromagnetic diffraction modeling in physics. The GPU architecture seems to be a suitable architecture to accelerate these convolutions, but reaching high application performance requires substantial development time and non-portable optimizations. In this work, we present the techniques, performance results and considerations to acceleratedoi:10.1007/978-3-642-24322-6_6 fatcat:b7u2jr3ap5clzpvjixhbxo36ca