Yuki Ogawa, Masahiro Iida, Motoki Amagasaki, Morihiro Kuga, Toshinori SueyoshiAuthors Info & Claims
Hardware acceleration significantly increases the performance of embedded systems built on programmable logic. Allowing a FPGA-based MicroBlaze processor to self-select the coprocessors it uses can help reduce area requirements and increase a system's ...
Convolutional neural network (CNN) has been widely deployed in deep learning networks at present. However, numerous convolution operations are computing intensive and often require powerful accelerator such as FPGA. The existed accelerators usually as ...
Recent advances in FPGA technology make them an attractive platform for accelerating scientific computing applications. We present a novel hardware accelerator for Quantum Monte Carlo simulations in N-body systems. The design is deeply pipelined and ...
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