Name
Abstract | ||
|---|---|---|
Vector processing is a widely used technique to improve performance and energy efficiency in modern processors. Most of them rely on predication to support divergence control. However, performance and energy consumption in predicated instructions are usually independent on the number of true values in a mask. This means that the efficiency of the system becomes sub-optimal as vector length increases. In this work we propose the Optimized Predication Execution (OPE) technique. OPE delays the execution of sparse masked vector instructions sharing the same PC, extracts their active elements and creates a new dense instruction with a higher mask density. After executing such dense instruction, results are restored to the original sparse instructions. Our approach improves performance by up to 25% and reduces dynamic energy consumption by up to 43% on real applications with predication. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/PACT.2019.00054 | 2019 28th International Conference on Parallel Architectures and Compilation Techniques (PACT) |
Keywords | Field | DocType |
Vector,SIMD,Data Level Parallelism,Power,Efficiency,DLP | Euclidean vector,Divergence,Computer science,Efficient energy use,Parallel computing,SIMD,Dynamic energy,Vector processor,Energy consumption,Out-of-order execution | Conference |
ISSN | ISBN | Citations |
1089-795X | 978-1-7281-3614-1 | 0 |
PageRank | References | Authors |
0.34 | 1 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Adrian Barredo | 1 | 0 | 2.37 |
| Juan Manuel Cebrian | 2 | 24 | 10.19 |
| Miquel Moretó | 3 | 0 | 0.68 |
| Marc Casas | 4 | 111 | 23.61 |
| Mateo Valero | 5 | 4520 | 355.94 |