View article

Gather and scatter are two fundamental data-parallel operations, where a large number of data items are read (gathered) from or are written (scattered) to given locations. In this paper, we study these two operations on graphics processing units (GPUs).

With superior computing power and high memory bandwidth, GPUs have become a commodity multiprocessor platform for general-purpose high-performance computing. However, due to the random access nature of gather and scatter, a naive implementation of the two operations suffers from a low utilization of the memory bandwidth and consequently a long, unhidden memory latency. Additionally, the architectural details of the GPUs, in particular, the memory hierarchy design, are unclear to the programmers. Therefore, we design multi-pass gather and scatter operations to improve their data access locality, and develop a performance model to help understand …