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Stencil computation is one of the important kernels in scientific computations, however, the sustained performance is limited by memory bandwidth especially on multi-core microprocessors and GPGPUs due to its small operationalintensity. In this paper, we propose a scalable streaming-array (SSA) of simple soft-processors for high-performance stencil computation on multiple FPGAs. The SSA architecture...
This paper evaluates the actual power consumption and the total energy for scientific floating-point computations accelerated by FPGA-based custom computing machines. With our FPGA-based machines: the streaming accelerator for computational fluid dynamics and the programmable systolic-array processor for numerical simulations based on difference schemes, we measure the power of the entire systems...
For numerical computations requiring a relatively high ratio of data access to operation, the scalability of memory bandwidth is key to performance improvement. In this paper, we propose a scalable FPGA-array to achieve custom computing machines for high-performance and power-efficient scientific simulations based on difference schemes. With the FPGA-array, we construct a systolic computational-memory...
This paper presents an FPGA-based streaming computation for the lattice Boltzmann method (LBM) to simulate fluid flow with floating-point calculations. LBM is suitable for streaming computation because of its parallelism and regularity. We optimize the equations of LBM, and then formulate a streaming computation. To design an efficient data-path for throughput and hardware resource utilization, we...
This paper presents an FPGA-based flow solver based on the systolic architecture. We show that the fractional-step method employing central difference schemes can be expressed as a systolic algorithm, and therefore the systolic architecture is suitable for a dedicated processor to the flow solver. We have designed a 2D systolic array of cells, each of which has a micro-programmable data-path containing...
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