C^2-bound: A Capacity and Concurrency driven Analytical Model for Manycore Design

Abstract

In this paper, we propose C2-Bound, a data-driven analytical model, that incorporates both memory capacity and data access concurrency factors to optimize many-core design. C2-Bound is characterized by combining the newly proposed latency model, concurrent average memory access time (C- AMAT), with the well-known memory-bounded speedup model (Sun-Ni's law) to facilitate computing tasks. Compared to tradi- tional chip designs that lack the notion of memory concurrency and memory capacity, C2-Bound model finds memory bound factors significantly impact the optimal number of cores as well as their optimal silicon area allocations, especially for data-intensive applications with a none parallelizable sequential portion. Therefore, our model is valuable to the design of new generation many-core architectures that target big data process- ing, where working sets are usually larger than conventional scientific computing. These findings are evidenced by our detailed simulations, which show with C2-Bound the design space can be narrowed down significantly up to four orders of magnitude. C2-Bound analytic results can be either used in reconfigurable hardware environments or, by software designers, applied to scheduling, partitioning, and allocating resources among diverse applications.

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