A memory access model for highly-threaded many-core architectures

Many-core architectures are excellent in hiding memory-access latency by low-overhead context switching among a large number of threads. The speedup of algorithms carried out on these machines depends on how well the latency is hidden. If the number of threads were infinite, then theoretically these machines should provide the performance predicted by the PRAM analysis of the programs. However, the number of allowable threads per processor is not infinite. In this paper, we introduce the Threaded Many-core Memory (TMM) model which is meant to capture the important characteristics of these highly-threaded, many-core machines. Since we model some important machine parameters of these machines, we expect analysis under this model to give more fine-grained performance prediction than the PRAM analysis. We analyze 4 algorithms for the classic all pairs shortest paths problem under this model. We find that even when two algorithms have the same PRAM performance, our model predicts different performance for some settings of machine parameters. For example, for dense graphs, the Floyd- Warshall algorithm and Johnson's algorithms have the same performance in the PRAM model. However, our model predicts different performance for large enough memory-access latency and validates the intuition that the Floyd-Warshall algorithm performs better on these machines.