Task management analysis on the CellBE

Abstract

There is a clear industrial trend towards chip multiprocessors (CMP) as the most power efficient way of further increasing performance. Heterogeneous CMP architectures take one more step along this power efficiency trend by using multiple types of processors, tailored to the workloads they will execute. Programming these CMP architectures has been identified as one of the main challenges in the near future, and programming heterogeneous systems is even more challenging. High-level programing models which allow the programmer to identify parallel tasks, and the runtime management of the intertask dependencies, have been identified as a suitable model for programming such heterogeneous CMP architectures. In this paper we analyze the performance of Cell Superscalar, a task-based programming model for the Cell architecture, in terms of its scalability to higher number of on-chip processors. Our results show that the low performance of the PPE component limits the scalability of some applications to less than 16 processors. Since the PPE has been identified as the limiting element, we perform a set of simulation studies evaluating the impact of out-of-order execution, and larger caches on the task management overhead.