Title :
SSDM: Smart Stack Data Management for software managed multicores (SMMs)
Author :
Jing Lu ; Ke Bai ; Shrivastava, Ashish
Author_Institution :
Compiler Microarchitecture Lab., Arizona State Univ., Tempe, AZ, USA
fDate :
May 29 2013-June 7 2013
Abstract :
Software Managed Multicore (SMM) architectures have been proposed as a solution for scaling the memory architecture. In an SMM architecture, there are no caches, and each core has only a local scratchpad memory. If all the code and data of the task to be executed on an SMM core cannot fit on the local memory, then data must be managed explicitly in the program through DMA instructions. While all code and data need to be managed, an efficient technique to manage stack data is of utmost importance since an average of 64% of all accesses may be to stack variables [16]. In this paper, we formulate the problem of stack data management optimization on an SMM core. We then develop both an ILP and a heuristic - SSDM (Smart Stack Data Management) to find out where to insert stack data management calls in the program. Experimental results demonstrate SSDM can reduce the overhead by 13X over the state-of-the-art stack data management technique [10].
Keywords :
digital storage; microprocessor chips; multiprocessing systems; DMA instructions; SSDM; smart stack data management; software managed multicores; Benchmark testing; Libraries; Memory architecture; Memory management; Multicore processing; Software; SPM; Stack data; embedded systems; local memory; multi-core processor; scratchpad memory;
Conference_Titel :
Design Automation Conference (DAC), 2013 50th ACM/EDAC/IEEE
Conference_Location :
Austin, TX