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| Content Provider | ACM Digital Library |
|---|---|
| Author | Abbaspour, Sahar Jordan, Alexander Schoeberl, Martin |
| Abstract | In a real-time system, the use of a scratchpad memory can mitigate the difficulties related to analyzing data caches, whose behavior is inherently hard to predict. We propose to use a scratchpad memory for stack allocated data. While statically allocating stack frames for individual functions to scratchpad memory regions aids predictability, it is limited to non-recursive programs and static allocation has to take different calling contexts into account. Using a stack cache that dynamically spills data to and fills data from external memory avoids these problems, while its simple design allows for efficiently deriving worst-case bounds through static analysis. In this paper we present the design and implementation of software managed caching of stack allocated data in a scratchpad memory. We demonstrate a compiler-aided implementation of a stack cache using the LLVM compiler framework and report on its efficiency. Our evaluation encompasses stack management overhead and impact on worst-case execution time analysis. The state-of-the-art worst-case execution time analysis tool aiT is able to correctly classify all stack cache accesses as accesses to the scratchpad memory. |
| Starting Page | 319 |
| Ending Page | 326 |
| Page Count | 8 |
| File Format | |
| ISBN | 9781450347877 |
| DOI | 10.1145/2997465.2997488 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2016-10-19 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Real-time systems Wcet analysis Scratchpad memory Stack caching |
| Content Type | Text |
| Resource Type | Article |
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