Name
Abstract | ||
|---|---|---|
Power and thermal limitations make it impossible to run all cores on a multicore system at their maximum frequency. Therefore, modern systems require careful power management. These systems must manage complex tradeoffs between energy, power, and frequency, choosing which cores to accelerate to achieve good performance while maintaining energy efficiency or operating under a power budget. Navigating these tradeoffs is especially hard with multi-threaded applications, where performance depends on the relative progress of parallel worker threads between synchronization points. Prior work on chip-level power management for multi-threaded applications has largely relied on indirect heuristics and metrics calculated from low-level performance counters to estimate each thread's progress. However, these indirect metrics are often inaccurate. Instead, we propose to gather progress information directly from software itself. We present ThreadBeats, a simple application-level annotation framework that directly and accurately conveys thread progress information to hardware. We design DVFS controllers that exploit ThreadBeats information for two purposes: (i) improving performance by equalizing thread progress and (ii) minimizing runtime under a power budget constraint. These controllers reduce wait time at barriers by 77% on average and improve energy-delay product under a power budget by 23% over prior work. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/ICCD.2017.87 | 2017 IEEE International Conference on Computer Design (ICCD) |
Keywords | Field | DocType |
power control,runtime power management,thread progress,software annotation | Power budget,Power management,Efficient energy use,Computer science,Power control,Real-time computing,Exploit,Thread (computing),Heuristics,Multi-core processor,Distributed computing | Conference |
ISSN | ISBN | Citations |
1063-6404 | 978-1-5386-2255-1 | 0 |
PageRank | References | Authors |
0.34 | 21 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sabrina M. Neuman | 1 | 18 | 1.40 |
| Jason E. Miller | 2 | 230 | 10.31 |
| Daniel Sanchez | 3 | 928 | 39.02 |
| Srinivas Devadas | 4 | 8606 | 1146.30 |