A PRAM-NUMA Model of Computation for Addressing Low-TLP Workloads
It is possible to implement the parallel random access machine (PRAM) on a chip multiprocessor (CMP) efficiently with an emulated shared memory (ESM) architecture to gain easy parallel programmability crucial to wider penetration of CMPs to general purpose computing. This implementation relies on exploitation of the slack of parallel applications to hide the latency of the memory system instead of caches, sufficient bisection bandwidth to guarantee high throughput, and hashing to avoid hot spots in intercommunication. Unfortunately this solution can not handle workloads with low thread-level parallelism (TLP) efficiently because then there is not enough parallel slackness available for hiding the latency. In this paper we show that integrating non-uniform memory access (NUMA) support to the PRAM implementation architecture can solve this problem and provide a natural way for migration of the legacy code written for a sequential or multi-core NUMA machine. The obtained PRAM-NUMA hybrid model is defined and architectural implementation of it is outlined on our ECLIPSE ESM CMP framework. A high-level programming language example is given.
Parallel computing; Computational models; Thread-level parallelism; PRAM; NUMA
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