Abstract
Limited energy and memory resources are important constraints in the design of an embedded system. Compression is an useful and widely employed mechanism to reduce the memory requirements of the system. As the leakage energy of a memory system increases with its size and because of the increasing contribution of leakage to overall system energy, compression also has a significant effect on reducing energy consumption. However, storing compressed data/instructions has a performance and energy overhead associated with decompression at runtime. The underlying compression algorithm, the corresponding implementation of the decompression and the ability to reuse decompressed information critically impact this overhead. In this paper, we explore the influence of compression on overall memory energy using a commercial embedded Java virtual machine (JVM) and a customized compression algorithm. Our results show that compression is effective in reducing energy even when considering the runtime decompression overheads for most applications.
| Original language | English (US) |
|---|---|
| Pages | 163-168 |
| Number of pages | 6 |
| State | Published - Sep 25 2002 |
| Event | Proceedings of the Tenth International Symposium on Hardware/Software Codesign: CODES 2002 - Estes Park, CO, United States Duration: May 6 2002 → May 8 2002 |
Other
| Other | Proceedings of the Tenth International Symposium on Hardware/Software Codesign: CODES 2002 |
|---|---|
| Country | United States |
| City | Estes Park, CO |
| Period | 5/6/02 → 5/8/02 |
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All Science Journal Classification (ASJC) codes
- Hardware and Architecture
Cite this
}
Energy savings through compression in embedded Java environments. / Chen, G.; Kandemir, Mahmut; Narayanan, Vijaykrishnan; Irwin, Mary Jane; Wolf, W.
2002. 163-168 Paper presented at Proceedings of the Tenth International Symposium on Hardware/Software Codesign: CODES 2002, Estes Park, CO, United States.Research output: Contribution to conference › Paper
TY - CONF
T1 - Energy savings through compression in embedded Java environments
AU - Chen, G.
AU - Kandemir, Mahmut
AU - Narayanan, Vijaykrishnan
AU - Irwin, Mary Jane
AU - Wolf, W.
PY - 2002/9/25
Y1 - 2002/9/25
N2 - Limited energy and memory resources are important constraints in the design of an embedded system. Compression is an useful and widely employed mechanism to reduce the memory requirements of the system. As the leakage energy of a memory system increases with its size and because of the increasing contribution of leakage to overall system energy, compression also has a significant effect on reducing energy consumption. However, storing compressed data/instructions has a performance and energy overhead associated with decompression at runtime. The underlying compression algorithm, the corresponding implementation of the decompression and the ability to reuse decompressed information critically impact this overhead. In this paper, we explore the influence of compression on overall memory energy using a commercial embedded Java virtual machine (JVM) and a customized compression algorithm. Our results show that compression is effective in reducing energy even when considering the runtime decompression overheads for most applications.
AB - Limited energy and memory resources are important constraints in the design of an embedded system. Compression is an useful and widely employed mechanism to reduce the memory requirements of the system. As the leakage energy of a memory system increases with its size and because of the increasing contribution of leakage to overall system energy, compression also has a significant effect on reducing energy consumption. However, storing compressed data/instructions has a performance and energy overhead associated with decompression at runtime. The underlying compression algorithm, the corresponding implementation of the decompression and the ability to reuse decompressed information critically impact this overhead. In this paper, we explore the influence of compression on overall memory energy using a commercial embedded Java virtual machine (JVM) and a customized compression algorithm. Our results show that compression is effective in reducing energy even when considering the runtime decompression overheads for most applications.
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M3 - Paper
SP - 163
EP - 168
ER -