POSTER: ξ-TAO: A cache-centric execution model and runtime for deep parallel multicore topologies

We have analyzed the ξ-TAO model and runtime with three benchmarks: a parallel hybrid quicksort/mergesort, a 2D Jacobi stencil, and the Unbalanced Tree Search (UTS) benchmark. We run ξ-TAO implementations of these benchmarks on a Dell PowerEdge R815 server with four AMD Opteron 6348 processors, totalling 8 NUMA nodes and 48 cores. Figure 2 shows the scalability of UTS+ξ-TAO compared to thread-centric runtimes based on work stealing (MassiveThreads [6], Intel TBB) and hierarchical WS+PDF (Qthreads [10]). UTS was implemented in ξ-TAO by grouping sibling nodes into a TAO and attaching a static scheduler. UTS has a very small working set, hence the best performance is achieved when each TAO is mapped to a single core (ξ-TAO-w1). The combination of tight reuse, pre-built task groups and static scheduling results in high scalability for UTS+ξ-TAO. Unlike UTS, the parallel sorting and 2D Jacobi benchmarks are memory intensive benchmarks. By selecting assemblies of width two (i.e., core-width of the L2 caches) and six (i.e., core-width of the L3 cache) ξ-TAO is able to outperform competing approaches thanks to better management of available memory bandwidth and shared cache capacity.