Name
Abstract | ||
|---|---|---|
Loop fusion combines corresponding iterations of different loops. It is traditionally used to decrease program run time, by reducing loop overhead and increasing data locality. In this paper, however, we consider its effect on energy. the uniformity, or balance of demand for system resources. On a conventional superscalar processor, increased balance tends to increase IPC, and thus dynamic power, so that fusion-induced improvements in program energy are slightly smaller than improvements in program run time. If IPC is held constant, however, by reducing frequency and voltage-particularly on a processor with multiple clock domains-then energy improvements may significantly exceed run time improvements. We demonstrate the benefits of increased program balance under a theoretical model of processor energy consumption. We then evaluate the benefits of fusion empirically on synthetic and real-world benchmarks, using our existing loop-fusing compiler and a heavily modified version of the SimpleScalar/Wattch simulator. For the real-world benchmarks, we demonstrate energy savings ranging from 7-40%, with run times ranging from 1% slowdown to 17% speedup. In addition to validating our theoretical model, the simulation results allow us to "tease apart" the factors that contribute to fusion-induced time and energy savings. |
Year | DOI | Venue |
|---|---|---|
2004 | 10.1109/PACT.2004.28 | IEEE PACT |
Keywords | Field | DocType |
energy impact,multiple clock domains-then energy,real-world benchmarks,program energy,energy saving,increased program balance,program run time,aggressive loop fusion,theoretical model,run time,fusion-induced time,processor energy consumption,instruction sets,loop fusion,parallel processing,resource allocation | Loop fusion,Computer science,Instruction set,Parallel computing,Compiler,Real-time computing,Dynamic demand,Resource allocation,Ranging,Energy consumption,Speedup | Conference |
ISBN | Citations | PageRank |
0-7695-2229-7 | 9 | 0.59 |
References | Authors | |
24 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| YongKang Zhu | 1 | 21 | 2.05 |
| Grigorios Magklis | 2 | 702 | 45.64 |
| Michael L. Scott | 3 | 2843 | 248.01 |
| Chen Ding | 4 | 422 | 28.21 |
| Albonesi, David H. | 5 | 2091 | 165.88 |