Abstract
Emerging computing architectures such as near-memory computing (NMC) promise improved performance for applications by reducing the data movement between CPU and memory. However, detecting such applications is not a trivial task. In this ongoing work, we extend the state-of-the-art platform-independent software analysis tool with NMC related metrics such as memory entropy, spatial locality, data-level, and basic-block-level parallelism. These metrics help to identify the applications more suitable for NMC architectures.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 22nd International Workshop on Software and Compilers for Embedded Systems, SCOPES 2019 |
| Editors | Sander Stuijk |
| Place of Publication | New York |
| Publisher | Association for Computing Machinery, Inc |
| Pages | 23-26 |
| Number of pages | 4 |
| ISBN (Electronic) | 978-1-4503-6762-2 |
| DOIs | |
| Publication status | Published - 27 May 2019 |
| Event | 22nd International Workshop on Software and Compilers for Embedded Systems, (SCOPES2019) - St. Goar, Germany Duration: 27 May 2019 → 28 May 2019 https://scopesconf.org/scopes-19/ |
Conference
| Conference | 22nd International Workshop on Software and Compilers for Embedded Systems, (SCOPES2019) |
|---|---|
| Abbreviated title | SCOPES2019 |
| Country | Germany |
| City | St. Goar |
| Period | 27/05/19 → 28/05/19 |
| Internet address |
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Keywords
- Application characterization
- LLVM IR
- Memory
- Near-Memory Computing
- Parallelism
Cite this
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Memory and parallelism analysis using a platform-independent approach. / Corda, Stefano; Singh, Gagandeep; Awan, Ahsan Javed; Jordans, Roel; Corporaal, Henk.
Proceedings of the 22nd International Workshop on Software and Compilers for Embedded Systems, SCOPES 2019. ed. / Sander Stuijk. New York : Association for Computing Machinery, Inc, 2019. p. 23-26.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review
TY - GEN
T1 - Memory and parallelism analysis using a platform-independent approach
AU - Corda, Stefano
AU - Singh, Gagandeep
AU - Awan, Ahsan Javed
AU - Jordans, Roel
AU - Corporaal, Henk
PY - 2019/5/27
Y1 - 2019/5/27
N2 - Emerging computing architectures such as near-memory computing (NMC) promise improved performance for applications by reducing the data movement between CPU and memory. However, detecting such applications is not a trivial task. In this ongoing work, we extend the state-of-the-art platform-independent software analysis tool with NMC related metrics such as memory entropy, spatial locality, data-level, and basic-block-level parallelism. These metrics help to identify the applications more suitable for NMC architectures.
AB - Emerging computing architectures such as near-memory computing (NMC) promise improved performance for applications by reducing the data movement between CPU and memory. However, detecting such applications is not a trivial task. In this ongoing work, we extend the state-of-the-art platform-independent software analysis tool with NMC related metrics such as memory entropy, spatial locality, data-level, and basic-block-level parallelism. These metrics help to identify the applications more suitable for NMC architectures.
KW - Application characterization
KW - LLVM IR
KW - Memory
KW - Near-Memory Computing
KW - Parallelism
UR - http://www.scopus.com/inward/record.url?scp=85066027586&partnerID=8YFLogxK
U2 - 10.1145/3323439.3323988
DO - 10.1145/3323439.3323988
M3 - Conference contribution
AN - SCOPUS:85066027586
SP - 23
EP - 26
BT - Proceedings of the 22nd International Workshop on Software and Compilers for Embedded Systems, SCOPES 2019
A2 - Stuijk, Sander
PB - Association for Computing Machinery, Inc
CY - New York
ER -