REEL: Reducing effective execution latency of floating point operations

Abstract

The height of the dynamic dependence graph of a program, as executed by a processor, determines the minimum bound on the execution time. This height can be decreased by reducing the effective execution latency of operations that form dependence chains in the graph. In this paper, we propose a technique called REEL to reduce overall latency of chains of dependent floating point (FP) operations by increasing the throughput of computation. REEL comprises of a high-throughput floating point unit (HFP) that allows early issue of an FP Add that is dependent on another FP Add or FP Multiply. This is complemented by instruction scheduler modifications that allow early issue of dependent FP Adds, and a novel checker logic that corrects any precision errors. Unlike conventional static operation fusion, like fused Multiply-Add (FMA), there are no changes to the instruction set to enable utilization of the new hardware, and no recompilation is necessary. Furthermore, unlike ISA-level FMA, our technique produces results that are bit compatible while boosting performance of Add-Add dependence pairs in addition to Multiply-Add pairs. Our evaluation of REEL using CFP2006 benchmarks shows an average performance gain of 7.6% and maximum performance gain of 17% while consuming 1.2% lower energy.