Improving Dynamic Memory Allocation on Many-Core Embedded Systems With Distributed Shared Memory

Abstract

Memory management on many-core architectures is a major challenge for improving the overall system performance. Memory resources are distributed over nodes for faster local accesses. Dynamic workloads heavily depend on memory requests and inefficient memory management leads to severe bottlenecks and performance degradation. In this paper, we focus on optimizing dynamic memory allocation on such platforms and present a scalable, microcode-accelerated distributed dynamic memory manager. The proposed manager exploits the presence of a hardware accelerator while offering a C application programming interface to application developers. Experimental results show performance gains on average 10% compared to allocators written purely in C and sufficient scalability as platform size increases.