Title
Memory Sizing of a Scalable SRAM In-Memory Computing Tile Based Architecture
Abstract
Modern computing applications require more and more data to be processed. Unfortunately, the trend in memory technologies does not scale as fast as the computing performances, leading to the so called memory wall. New architectures are currently explored to solve this issue, for both embedded and off-chip memories. Recent techniques that bringing computing as close as possible to the memory array such as, In-Memory Computing (IMC), Near-Memory Computing (NMC), Processing-In-Memory (PIM), allow to reduce the cost of data movement between computing cores and memories. For embedded computing, In-Memory Computing scheme presents advantageous computing and energy gains for certain class of applications. However, current solutions are not scaling to large size memories and high amount of data to compute. In this paper, we propose a new methodology to tile a SRAM/IMC based architecture and scale the memory requirements according to an application set. By using a high level LLVM-based simulation platform, we extract IMC memory requirements for a certain class of applications. Then, we detail the physical and performance costs of tiling SRAM instances. By exploring multi-tile SRAM Place&Route in 28nm FD-SOI, we explore the respective performance, energy and cost of memory interconnect. As a result, we obtain a detailed wire cost model in order to explore memory sizing trade-offs. To achieve a large capacity IMC memory, by splitting the memory in multiple sub-tiles, we can achieve lower energy (up to 78% gain) and faster (up to 49% gain) IMC tile compared to a single large IMC memory instance.
Year
DOI
Venue
2019
10.1109/VLSI-SoC.2019.8920373
2019 IFIP/IEEE 27th International Conference on Very Large Scale Integration (VLSI-SoC)
Keywords
Field
DocType
In-Memory Computing,Near Memory Computing,SRAM,interconnect,wire-cost
Cryptography,Computer science,In-Memory Processing,Static random-access memory,Memory management,Sizing,Interconnection,Pattern matching,Embedded system,Scalability
Conference
ISSN
ISBN
Citations 
2324-8432
978-1-7281-3916-6
2
PageRank 
References 
Authors
0.39
7
7
Name
Order
Citations
PageRank
R. Gauchi120.39
Maha Kooli220.39
Pascal Vivet360653.09
Jean-Philippe Noël4237.54
Edith Beigne553652.54
Subhasish Mitra63657228.90
H. -P. Charles720.39