For the HPC community, common issues on computational speed and computational accuracy are generally considered to be conflicting. However, the diversity and enhancement of hardware and the high productivity of software have allowed users to choose the precision within the requirement of appropriate computational accuracy. These may provide us with enormous changes in scientific and technical computing, whereas it has been dominated by double-precision calculation for a long time. In the seminar, I will introduce the recent topics such as the relationship between high performance and precision and the relationship between modern hardware and computation accuracy, mainly focusing on the numerical libraries developed by my team in the above topics; i) establishment of higher precision software by massively-and-high-performance low-precision computing units, ii) algorithmic advancement of lower-precision units in scientific computing like HPL-AI benchmark, iii) idea of minimal-precision computing. The first is the realization of a DGEMM-equivalent matrix product using TensorCore(TC) by Mukunoki et al. This is an important fact. It is one of the academic case studies of the utilization of TC's. On the other hand, it suggests the possibility of controlling the number of double precision units by installing a sufficient number of low precision arithmetic units. The second refers to our HPL-AI result, of course, one of the world's four crowning benchmarks and its computation is based on a mixed precision of FP16, FP32, and FP64 formats. The essential point of HPL-AI is to bring out the high performance of low-precision arithmetic while preventing numerical instability and inaccuracy in low-precision arithmetic. It is not simply a matter of rewriting double to half. This is accomplished by a preliminary analysis of the computation target and patterns. The third is to promote the minimum system of computation, which is anticipated to change storage capacity, energy consumption, and minimum hardware requirements of the current floating-point unit. Users won't feel a big impact in terms of input/output, but the internal design of computers will be significantly enhanced.

注意事項:
・参加の際はPCマイクの音声・ビデオをオフにされるようお願いいたします。
・当日の会場環境や通信状態により、やむなく配信を中止・中断する場合がございます。
・プログラムの内容、時間は予告なく変更される場合があります。
・ご使用の機器やネットワークの環境によっては、ご視聴いただけない場合がございます。
・インターネット中継に関する著作権は、主催者及び発表者に帰属します。なお、配信された映像及び音声、若しくはその内容を、理化学研究所の許可無くほかのウェブサイトや著作物等への転載，複製，改変等を行うことを禁じます。