High performance GPU concurrent B+tree

Abstract

Concurrent B+trees have been widely used in many systems from file systems to databases. With the volume of data requests expanding exponentially, the systems are facing tremendous performance pressure. GPUs have shown their potential to accelerate the concurrent B+trees operations with their high volume of parallel computing resources and large memory bandwidth. In concurrent B+tree, the conflicts should be detected and resolved when multiple concurrent requests are traversing and operating on the tree. However, conflict detection and handling in concurrent B+tree complicates the request processing logic, increases the number of memory accesses and leads to execution path divergence. That leads to performance degradation and increased response time variance.