Architecture Optimization of Application-Specific Implicit Instructions

A Di Biagio, G Agosta, M Sykora… - ACM Transactions on …, 2012 - dl.acm.org
A Di Biagio, G Agosta, M Sykora, C Silvano
ACM Transactions on Embedded Computing Systems (TECS), 2012dl.acm.org
Dynamic configuration of application-specific implicit instructions has been proposed to
better exploit the available parallelism at the instruction level in pipelined processors. The
support of such implicit instruction issue-requires the pipeline to be extended with a trigger
table that describes the instruction implicitly issued as a response to a value written into a
triggering register by a triggering instruction (which may be an add or sub instruction). In this
article, we explore the design optimization of the trigger table to maximize the number of …
Dynamic configuration of application-specific implicit instructions has been proposed to better exploit the available parallelism at the instruction level in pipelined processors. The support of such implicit instruction issue-requires the pipeline to be extended with a trigger table that describes the instruction implicitly issued as a response to a value written into a triggering register by a triggering instruction (which may be an add or sub instruction). In this article, we explore the design optimization of the trigger table to maximize the number of instructions that can be implicitly issued while keeping the limited size of the trigger table. The concept of implicitly issued instruction has been formally defined by considering the inter-basic block analysis of control and data dependencies. A compilation tool chain has been developed to automatically identify the optimization opportunities, taking into account the constraints imposed by control and data dependencies as well as by architectural limitations. The proposed solutions have been applied to the case of a baseline scalar MIPS processor where, for the selected set of benchmarks (DSPStone and Mibench/automotive), we obtained an average speedup of 17%.
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