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| Content Provider | ACM Digital Library |
|---|---|
| Author | Shrivastava, Aviral Bai, Ke |
| Abstract | This paper presents a scheme to manage heap data in the local memory present in each core of a limited local memory (LLM) multi-core processor. While it is possible to manage heap data semi-automatically using software cache, managing heap data of a core through software cache may require changing the code of the other threads. Cross thread modifications are difficult to code and debug, and only become more difficult as we scale the number of cores. We propose a semi-automatic, and scalable scheme for heap data management that hides this complexity in a library with a much natural programming interface. Furthermore, for embedded applications, where the maximum heap size can be known at compile time, we propose optimizations on the heap management to significantly improve the application performance. Experiments on several benchmarks of MiBench executing on the Sony Playstation 3 show that our scheme is easier to use, and if we know the maximum size of heap data, then our optimizations can improve application performance by an average of 14%. |
| Starting Page | 317 |
| Ending Page | 326 |
| Page Count | 10 |
| File Format | |
| ISBN | 9781605589053 |
| DOI | 10.1145/1878961.1879015 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2010-10-24 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Local memory Ibm cell Scratch pad memory Mpi Multi-core programming Distributed memory processor Heap data management |
| Content Type | Text |
| Resource Type | Article |
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