Training convolutional neural networks (CNNs) on large sets of high-resolution images is too computationally intense to be performed on commodity CPUs. Such architectures however ...
Pattern recognition and computer vision tasks are computationally intensive, repetitive, and often exceed the capabilities of the CPU, leaving little time for higher level tasks. ...
We explore the application of Small-Scale Reconfigurability (SSR) to graphics hardware. SSR is an architectural technique wherein functionality common to multiple subunits is reuse...
Kevin Dale, Jeremy W. Sheaffer, Vinu Vijay Kumar, ...
Field programmable gate arrays (FPGAs), graphics processing units (GPUs) and Sony's PlayStation 2 vector units offer scope for hardware acceleration of applications. We compa...
Lee W. Howes, Paul Price, Oskar Mencer, Olav Beckm...
A significant obstacle to the widespread adoption of FPGAbased configurable computing hardware has been the difficulty of mapping applications onto this hardware. We are developin...
Benjamin A. Levine, Senthil Natarajan, Chandra Tan...