Combinatorics and Geometry for the Many-ported, Distributed and Shared Memory Architecture
Hao Luan, Alan Gatherer

TL;DR
This paper proposes a hierarchical, distributed memory architecture for manycore SoCs that improves throughput, reduces latency and area, and simplifies physical design by combining combinatorial and geometric analysis.
Contribution
It introduces a novel architecture that integrates combinatorial and geometric insights, enabling scalable, efficient, and physically realizable shared memory systems for manycore SoCs.
Findings
Supports 20% higher throughput
Achieves 20% lower latency
Reduces interconnection area by 30%
Abstract
Manycore SoC architectures based on on-chip shared memory are preferred for flexible and programmable solutions in many application domains. However, the development of many ported memory is becoming increasingly challenging as we approach the end of Moore's Law while systems requirements demand larger shared memory and more access ports. Memory can no longer be designed simply to minimize single transaction access time, but must take into account the functionality on the SoC. In this paper we examine a common large memory usage in SoC, where the memory is used as storage for large buffers that are then moved for time scheduled processing. We merge two aspects of many ported memory design, combinatorial analysis of interconnect, and geometric analysis of critical paths, extending both to show that in this case the SoC performance benefits significantly from a hierarchical, distributed…
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Taxonomy
TopicsInterconnection Networks and Systems · Parallel Computing and Optimization Techniques · Low-power high-performance VLSI design
