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| Content Provider | ACM Digital Library |
|---|---|
| Author | Li, Lian Xue, Jingling |
| Abstract | Energy-aware compilers are becoming increasingly important for embedded systems due to the need to meet conflicting constraints on time, code size and power consumption. We introduce a trace-based, offline compiler framework on binaries and demonstrate its benefits in supporting energy optimisations. The key innovation lies in identifying frequently executed paths in a binary program and duplicating them as single-entry traces. Separating frequently from infrequently executed paths enables the compiler to focus both performance and energy optimisations on the hot traces.Traces constructed at the level of binaries are inherently inter-procedural, spanning both application and library code. Such a framework allows an embedded application developer to exploit optimisation opportunities made possible due to the information that is available only at link time.We describe the implementation of our trace-based framework in alto, a link-time optimiser for the Alpha architecture. We present a new algorithm for constructing the hot traces from binaries. This algorithm is both effective (since the execution cycles are mostly spent on traces) and practical (due to small code size increases caused). We have developed and implemented a new optimisation to reduce the functional unit leakage energy. We show how the traces facilitate the development of such an optimisation, which results in significant leakage energy savings for benchmark programs at the cost of small performance penalties. |
| Starting Page | 95 |
| Ending Page | 106 |
| Page Count | 12 |
| File Format | |
| ISBN | 1581138067 |
| DOI | 10.1145/997163.997178 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2004-06-11 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Trace Link-time optimisation Energy optimisation Binary translation Profile-guided optimisation |
| Content Type | Text |
| Resource Type | Article |
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