FRSZ2用于GPU上GMRES内部的寄存器内块压缩
FRSZ2 for In-Register Block Compression Inside GMRES on GPUs
AI总结：
本文提出轻量级寄存器内压缩器FRSZ2，在GPU上GMRES求解器中替代低精度压缩Krylov基，在保持最终精度的同时实现更大运行时节省。
摘要：
GMRES迭代求解器在GPU上的性能受限于GPU主存带宽。Compressed Basis GMRES通过以低精度存储Krylov基来减少内存访问，从而优于GMRES。一个悬而未决的问题是，比转换为低精度更复杂的压缩技术能否在保持最终结果精度的同时实现大量运行时节省。本文提出了轻量级寄存器内压缩器FRSZ2，它能够以现代NVIDIA H100 GPU的带宽速度进行解压。在实验评估中，我们证明使用FRSZ2代替低精度来压缩Krylov基可以带来更大的运行时收益，且不影响最终精度。
英文摘要：
The performance of the GMRES iterative solver on GPUs is limited by the GPU main memory bandwidth. Compressed Basis GMRES outperforms GMRES by storing the Krylov basis in low precision, thereby reducing the memory access. An open question is whether compression techniques that are more sophisticated than casting to low precision can enable large runtime savings while preserving the accuracy of the final results. This paper presents the lightweight in-register compressor FRSZ2 that can decompress at the bandwidth speed of a modern NVIDIA H100 GPU. In an experimental evaluation, we demonstrate using FRSZ2 instead of low precision for compression of the Krylov basis can bring larger runtime benefits without impacting final accuracy.
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