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Communication-avoidant Matrix Calculation Algorithm

Research and development of algorithms suitable for massively parallel computers

With the spread of massively parallel computers, it has become increasingly important to reduce the communication time associated with parallel computation. In this research, we aim to improve the performance of matrix computation algorithms by using an approach called “Communication Avoiding (CAA).”

Research

With parallel processing using large-scale parallel computers, the data communication time is often more important than the computation time. In particular, the large communication latency (the cost incurred regardless of the amount of data to be communicated) has become a problem, and there is a strong need to reduce the communication frequency (communication avoidance). We are reviewing existing matrix computation algorithms from the viewpoint of communication avoidance, and are researching and developing new algorithms for massively parallel computers that reduce the communication frequency.

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Takeshi Fukaya Associate Professor

Faculty of Information Initiative Center

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