TY - GEN
T1 - SmartApps
T2 - 13th International Workshop on Languages and Compilers for Parallel Computing, LCPC 2000
AU - Rauchwerger, Lawrence
AU - Amato, Nancy M.
AU - Torrellas, Josep
N1 - Publisher Copyright:
© Springer-Verlag Berlin Heidelberg 2001.
PY - 2001
Y1 - 2001
N2 - State-of-the-art run-time systems are a poor match to diverse, dynamic distributed applications because they are designed to provide support to a wide variety of applications, without much customization to individual specific requirements. Little or no guiding information flows directly from the application to the run-time system to allow the latter to fully tailor its services to the application. As a result, the performance is disappointing. To address this problem, we propose application-centric computing, or SMART APPLICATIONS. In the executable of smart applications, the compiler embeds most run-time system services, and a performance-optimizing feedback loop that monitors the application’s performance and adaptively reconfigures the application and the OS/hardware platform. At run-time, after incorporating the code’s input and the system’s resources and state, the SmartApp performs a global optimization. This optimization is instance specific and thus much more tractable than a global generic optimization between application, OS and hardware. The resulting code and resource customization should lead to major speedups. In this paper, we first describe the overall architecture of Smartapps and then present the achievements to date: Run-time optimizations, performance modeling, and moderately reconfigurable hardware.
AB - State-of-the-art run-time systems are a poor match to diverse, dynamic distributed applications because they are designed to provide support to a wide variety of applications, without much customization to individual specific requirements. Little or no guiding information flows directly from the application to the run-time system to allow the latter to fully tailor its services to the application. As a result, the performance is disappointing. To address this problem, we propose application-centric computing, or SMART APPLICATIONS. In the executable of smart applications, the compiler embeds most run-time system services, and a performance-optimizing feedback loop that monitors the application’s performance and adaptively reconfigures the application and the OS/hardware platform. At run-time, after incorporating the code’s input and the system’s resources and state, the SmartApp performs a global optimization. This optimization is instance specific and thus much more tractable than a global generic optimization between application, OS and hardware. The resulting code and resource customization should lead to major speedups. In this paper, we first describe the overall architecture of Smartapps and then present the achievements to date: Run-time optimizations, performance modeling, and moderately reconfigurable hardware.
UR - http://www.scopus.com/inward/record.url?scp=84958747430&partnerID=8YFLogxK
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U2 - 10.1007/3-540-45574-4_6
DO - 10.1007/3-540-45574-4_6
M3 - Conference contribution
AN - SCOPUS:84958747430
SN - 3540428623
SN - 9783540455745
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 82
EP - 96
BT - Languages and Compilers for Parallel Computing - 13th International Workshop, LCPC 2000, Revised Papers
A2 - Ferrante, Jeanne
A2 - Midkiff, Samuel P.
A2 - Moreira, Jose E.
A2 - Gupta, Manish
A2 - Chatterjee, Siddhartha
A2 - Prins, Jan
A2 - Pugh, William
A2 - Tseng, Chau-Wen
PB - Springer
Y2 - 10 August 2000 through 12 August 2000
ER -