A Case for In-Memory Random Scatter-Gather for Fast Graph Processing

Abstract

Because of the widely recognized memory wall issue, modern DRAMs are increasingly being assigned innovative functionalities beyond the basic read and write operations. Often referred to as “function-in-memory”, these techniques are crafted to leverage the abundant internal bandwidth available within the DRAM. However, these techniques face several challenges, including requiring large areas for arithmetic units and the necessity of splitting a single word into multiple pieces. These challenges severely limit the practical application of these function-in-memory techniques. In this paper, we present Piccolo, an efficient design of random scatter-gather memory. Our method achieves significant improvements with minimal overhead. By demonstrating our technique on a graph processing accelerator, we show that Piccolo and the proposed accelerator achieves $1.2-3.1 \times$ speedup compared to the prior art.