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.
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第199回 第2部

第199回 第2部
日時: 2020年10月5日(月)、16:40 - 17:00
(17:20 - 17:40 講演者を交えたフリーディスカッション(冒頭に1-2分の小休止を挟みます))
場所: BlueJeansによる遠隔セミナー
・講演題目:Recent topics of High Precision and Low Precision Computing in HPC
・講演者:今村 俊幸(大規模並列数値計算技術研究チーム、チームリーダー)
※発表・スライド共に英語