Name
Abstract | ||
|---|---|---|
Web 2.0 applications written in JavaScript are increasingly popular as they are easy to use, easy to update and maintain, and portable across a wide variety of computing platforms. Web applications receive frequent input from a rich array of sensors, network, and user input modalities. To handle the resulting asynchrony due to these inputs, web applications are developed using an event-driven programming model. These event-driven web applications have dramatically different characteristics, which provides an opportunity to create a customized processor core to improve the responsiveness of web applications. In this paper, we take one step towards creating a core customized to event-driven applications. We observe that instruction cache misses of web applications are substantially higher than conventional server and desktop workloads due to large working sets caused by distant re-use. To mitigate this bottleneck, we propose an instruction prefetcher (EFetch) that is tuned to exploit the characteristics of web applications. We find that an event signature, which captures the current event and function calling context, is a good predictor of the control flow inside a function of an event-driven program. It allows us to accurately predict a function's callees and their function bodies and prefetch them in a timely manner. For a set of real-world web applications, we show that the proposed prefetcher outperforms commonly implemented next-2-line prefetcher by 17%. Also, it consumes 5.2 times less area than a recently proposed prefetcher, while outperforming it. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1145/2628071.2628103 | PACT |
Keywords | Field | DocType |
cache memories,event-driven web applications,instruction prefetching,javascript | Mashup,Cache,Web analytics,Computer science,Parallel computing,Real-time computing,Ajax,Web 2.0,Web application,Web-based simulation,Web service | Conference |
ISSN | ISBN | Citations |
1089-795X | 978-1-5090-6607-0 | 10 |
PageRank | References | Authors |
0.51 | 20 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Gaurav Chadha | 1 | 30 | 1.67 |
| Scott Mahlke | 2 | 4811 | 312.08 |
| Satish Narayanasamy | 3 | 1040 | 44.36 |