Workload and network-optimized computing systems

D. P. LaPotin, S. Daijavad, C. L. Johnson, S. W. Hunter, K. Ishizaki, H. Franke, H. D. Achilles, D. P. Dumarot, N. A. Greco, B. Davari
IBM Research Division, Austin Research Laboratory, Austin, TX
IBM Journal of Research and Development, Volume 54 Issue 1, January 2010


   title={Workload and network-optimized computing systems},

   author={LaPotin, DP and Daijavad, S. and Johnson, CL and Hunter, SW and Ishizaki, K. and Franke, H. and Achilles, HD and Dumarot, DP and Greco, NA and Davari, B.},

   journal={IBM Journal of Research and Development},







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This paper describes a recent system-level trend toward the use of massive on-chip parallelism combined with efficient hardware accelerators and integrated networking to enable new classes of applications and computing-systems functionality. This system transition is driven by semiconductor physics and emerging network-application requirements. In contrast to general-purpose approaches, workload and network-optimized computing provides significant cost, performance, and power advantages relative to historical frequency-scaling approaches in a serial computational model. We highlight the advantages of on-chip network optimization that enables efficient computation and new services at the network edge of the data center. Software and application development challenges are presented, and a service-oriented architecture application example is shown that characterizes the power and performance advantages for these systems. We also discuss a roadmap for next-generation systems that proportionally scale with future networking bandwidth growth rates and employ 3-D chip integration methods for design flexibility and modularity.
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