The Sparse Data Reduction Engine

Sparse data and irregular data access patterns are hugely important to many applications, such as molecular dynamics and data analytics. Accelerating applications with these characteristics requires maximizing usable bandwidth at all levels of the memory hierarchy, reducing latency, maximizing reuse of moved data, and minimizing the amount the data is moved in the irst place. Many specialized data structures have evolved to meet these requisites for speciic applications, however, there are no general solutions for improving the performance of sparse applications. The structure of the memory hierarchy itself, conspires against general hardware for accelerating sparse applications, being designed for eicient bulk transport of data versus one byte at a time. This paper presents a general solution for a programmable data rearrangement/reduction engine near-memory to deliver bulk byte-addressable data access. The key technology presented in this paper is the Sparse Data Reduction Engine (SPDRE), which builds previous similar eforts to provide a practical near-memory reorganization engine. In addition to the primary contribution, this paper describes a programmer interface that enables all combinations of rearrangement, analysis of the methodology on a small series of applications, and inally a discussion of future work.