Abstract
The computer industry is moving towards two extremes: extremely high-performance high-throughput cloud computing, and low-power mobile computing. Cloud computing, while providing high performance, is very costly. Google and Microsoft Bing spend billions of dollars each year to maintain their server farms, mainly due to the high power bills. On the other hand, mobile computing is under a very tight energy budget, but yet the end users demand ever increasing performance on these devices. This trend indicates that conventional architectures are not able to deliver high-performance and low power consumption at the same time, and we need a new architecture model to address the needs of both extremes. In this paper, we thus introduce our Extremely Heterogeneous Architecture (EHA) project: EHA is a novel architecture that incorporates both general-purpose and specialized cores on the same chip. The general-purpose cores take care of generic control and computation. On the other hand, the specialized cores, including GPU, hard accelerators (ASIC accelerators), and soft accelerators (FPGAs), are designed for accelerating frequently used or heavy weight applications. When acceleration is not needed, the specialized cores are turned off to reduce power consumption. We demonstrate that EHA is able to improve performance through acceleration, and at the same time reduce power consumption. Since EHA is a heterogeneous architecture, it is suitable for accelerating heterogeneous workloads on the same chip. For example, data centers and clouds provide many services, including media streaming, searching, indexing, scientific computations. The ultimate goal of the EHA project is two-fold: first, to design a chip that is able to run different cloud services on it, and through this design, we would be able to greatly reduce the cost, both recurring and non-recurring, of data centers\clouds, second, to design a light-weight EHA that runs on mobile devices, providing end users with improved experience even under tight battery budget constraints.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 2012 International Symposium on Pervasive Systems, Algorithms, and Networks, I-SPAN 2012 |
| Pages | 30-36 |
| Number of pages | 7 |
| DOIs | |
| Publication status | Published - 2012 Dec 1 |
| Event | 12th International Symposium on Pervasive Systems, Algorithms, and Networks, I-SPAN 2012 - San Marcos, TX, United States Duration: 2012 Dec 13 → 2012 Dec 15 |
Publication series
| Name | Proceedings of the 2012 International Symposium on Pervasive Systems, Algorithms, and Networks, I-SPAN 2012 |
|---|
Other
| Other | 12th International Symposium on Pervasive Systems, Algorithms, and Networks, I-SPAN 2012 |
|---|---|
| Country | United States |
| City | San Marcos, TX |
| Period | 12/12/13 → 12/12/15 |
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All Science Journal Classification (ASJC) codes
- Computer Networks and Communications
- Applied Mathematics
Cite this
}
EHA : The extremely heterogeneous architecture. / Liu, Shaoshan; Ro, Won Woo; Liu, Chen; Salas, Alfredo C.; Cerin, Christophe; Han, Jian Jun; Gaudiot, Jean Luc.
Proceedings of the 2012 International Symposium on Pervasive Systems, Algorithms, and Networks, I-SPAN 2012. 2012. p. 30-36 6428802 (Proceedings of the 2012 International Symposium on Pervasive Systems, Algorithms, and Networks, I-SPAN 2012).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - EHA
T2 - The extremely heterogeneous architecture
AU - Liu, Shaoshan
AU - Ro, Won Woo
AU - Liu, Chen
AU - Salas, Alfredo C.
AU - Cerin, Christophe
AU - Han, Jian Jun
AU - Gaudiot, Jean Luc
PY - 2012/12/1
Y1 - 2012/12/1
N2 - The computer industry is moving towards two extremes: extremely high-performance high-throughput cloud computing, and low-power mobile computing. Cloud computing, while providing high performance, is very costly. Google and Microsoft Bing spend billions of dollars each year to maintain their server farms, mainly due to the high power bills. On the other hand, mobile computing is under a very tight energy budget, but yet the end users demand ever increasing performance on these devices. This trend indicates that conventional architectures are not able to deliver high-performance and low power consumption at the same time, and we need a new architecture model to address the needs of both extremes. In this paper, we thus introduce our Extremely Heterogeneous Architecture (EHA) project: EHA is a novel architecture that incorporates both general-purpose and specialized cores on the same chip. The general-purpose cores take care of generic control and computation. On the other hand, the specialized cores, including GPU, hard accelerators (ASIC accelerators), and soft accelerators (FPGAs), are designed for accelerating frequently used or heavy weight applications. When acceleration is not needed, the specialized cores are turned off to reduce power consumption. We demonstrate that EHA is able to improve performance through acceleration, and at the same time reduce power consumption. Since EHA is a heterogeneous architecture, it is suitable for accelerating heterogeneous workloads on the same chip. For example, data centers and clouds provide many services, including media streaming, searching, indexing, scientific computations. The ultimate goal of the EHA project is two-fold: first, to design a chip that is able to run different cloud services on it, and through this design, we would be able to greatly reduce the cost, both recurring and non-recurring, of data centers\clouds, second, to design a light-weight EHA that runs on mobile devices, providing end users with improved experience even under tight battery budget constraints.
AB - The computer industry is moving towards two extremes: extremely high-performance high-throughput cloud computing, and low-power mobile computing. Cloud computing, while providing high performance, is very costly. Google and Microsoft Bing spend billions of dollars each year to maintain their server farms, mainly due to the high power bills. On the other hand, mobile computing is under a very tight energy budget, but yet the end users demand ever increasing performance on these devices. This trend indicates that conventional architectures are not able to deliver high-performance and low power consumption at the same time, and we need a new architecture model to address the needs of both extremes. In this paper, we thus introduce our Extremely Heterogeneous Architecture (EHA) project: EHA is a novel architecture that incorporates both general-purpose and specialized cores on the same chip. The general-purpose cores take care of generic control and computation. On the other hand, the specialized cores, including GPU, hard accelerators (ASIC accelerators), and soft accelerators (FPGAs), are designed for accelerating frequently used or heavy weight applications. When acceleration is not needed, the specialized cores are turned off to reduce power consumption. We demonstrate that EHA is able to improve performance through acceleration, and at the same time reduce power consumption. Since EHA is a heterogeneous architecture, it is suitable for accelerating heterogeneous workloads on the same chip. For example, data centers and clouds provide many services, including media streaming, searching, indexing, scientific computations. The ultimate goal of the EHA project is two-fold: first, to design a chip that is able to run different cloud services on it, and through this design, we would be able to greatly reduce the cost, both recurring and non-recurring, of data centers\clouds, second, to design a light-weight EHA that runs on mobile devices, providing end users with improved experience even under tight battery budget constraints.
UR - http://www.scopus.com/inward/record.url?scp=84874594173&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84874594173&partnerID=8YFLogxK
U2 - 10.1109/I-SPAN.2012.11
DO - 10.1109/I-SPAN.2012.11
M3 - Conference contribution
SN - 9780769549309
T3 - Proceedings of the 2012 International Symposium on Pervasive Systems, Algorithms, and Networks, I-SPAN 2012
SP - 30
EP - 36
BT - Proceedings of the 2012 International Symposium on Pervasive Systems, Algorithms, and Networks, I-SPAN 2012
ER -