• Project Snapshot In this work, we aim to make RVV more accessible to scientific applications by integrating it into the RAJA performance-portability framework. • RAJA is a C++ library primarily developed at Lawrence Livermore National Laboratory that offers loop-based abstractions and multiple execution backends to deliver portable performance across heterogeneous systems. • We contribute a new RVV backend to RAJA’s vectorization API, enabling RVV-aware optimizations within RAJA-based applications. • In Their Own Words Poster Preview Meet the Authors Hung-Ming Lai PhD Student in Computer Science at National Tsing Hua University in Taiwan Hung-Ming is a PhD student in the Department of Computer Science, National Tsing-Hua University, Taiwan. • His thesis advisor is Prof. • His research interests are in compiler optimizations on RISC-V with SIMD computations, AI compiler optimizations, and compiler analysis for program reliability.

Article Summaries:

  • Project Snapshot In this work, we aim to make RVV more accessible to scientific applications by integrating it into the RAJA performance-portability framework. RAJA is a C++ library primarily developed at Lawrence Livermore National Laboratory that offers loop-based abstractions and multiple execution backends to deliver portable performance across heterogeneous systems. We contribute a new RVV backend to RAJA’s vectorization API, enabling RVV-aware optimizations within RAJA-based applications. In Their Own Words Poster Preview Meet the Authors Hung-Ming Lai PhD Student in Computer Science at

Sources: