TY - GEN
T1 - Automated task distribution in multicore network processors using statistical analysis
AU - Mallik, Arindam
AU - Zhang, Yu
AU - Memik, Gokhan
PY - 2007/12/1
Y1 - 2007/12/1
N2 - Chip multiprocessor designs are the most common types of architectures seen in Network Processors. As the Network Processors are used to implement increasingly complicated applications, task distribution among the cores is becoming an important problem. In this paper, we propose a new task allocation scheme for such architectures. This scheme relies on the inherent modular nature of the networking applications and intelligently distributes modules among different execution cores. Additionally, we selectively replicate modules to parallelize execution of tasks having longer processing time. We have developed a technique that uses the probability distribution of the execution times of different modules in the networking applications. The proposed schemes result in resource utilization of up to 95%, 89%, and 84% on average for the processors with 2, 4, and 8 cores, respectively. The schemes are highly scalable and can improve the throughput by 6.72 times for 8 core processors, aggregated over four representative applications. The combination of selective replication of modules and variation-aware task allocation result in up to 12.5% (9.9% on average) performance improvement as compared to a scheme based on just mean processing time.
AB - Chip multiprocessor designs are the most common types of architectures seen in Network Processors. As the Network Processors are used to implement increasingly complicated applications, task distribution among the cores is becoming an important problem. In this paper, we propose a new task allocation scheme for such architectures. This scheme relies on the inherent modular nature of the networking applications and intelligently distributes modules among different execution cores. Additionally, we selectively replicate modules to parallelize execution of tasks having longer processing time. We have developed a technique that uses the probability distribution of the execution times of different modules in the networking applications. The proposed schemes result in resource utilization of up to 95%, 89%, and 84% on average for the processors with 2, 4, and 8 cores, respectively. The schemes are highly scalable and can improve the throughput by 6.72 times for 8 core processors, aggregated over four representative applications. The combination of selective replication of modules and variation-aware task allocation result in up to 12.5% (9.9% on average) performance improvement as compared to a scheme based on just mean processing time.
UR - http://www.scopus.com/inward/record.url?scp=60649084031&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=60649084031&partnerID=8YFLogxK
U2 - 10.1145/1323548.1323563
DO - 10.1145/1323548.1323563
M3 - Conference contribution
AN - SCOPUS:60649084031
SN - 9781595939456
T3 - ANCS'07 - Proceedings of the 2007 ACM Symposium on Architecture for Networking and Communications
SP - 67
EP - 76
BT - ANCS'07 - Proceedings of the 2007 ACM Symposium on Architecture for Networking and Communications
T2 - 3rd ACM/IEEE Symposium on Architectures for Networking and Communications Systems, ANCS 2007
Y2 - 3 December 2007 through 4 December 2007
ER -