With the advent of the multicore era, it is clear that future growth in application performance
will primarily come from increased parallelism. We believe parallelism should be introduced …

In this paper, we address the problem of scheduling parallel tasks with general
synchronization patterns using a cooperative runtime. Current implementations for task …

We describe a progressive philosophy to help benchmark systems and designs in the High
Performance Computing (HPC) domain. These systems now include heterogeneous multi …

Despite tackling the memory and power walls over the last decades, new challenges for
manycore architectures arose due to the emergence of ever increasing memory …

Parallel libraries such as OpenMP distribute the iterations of parallel-for-loops among the
threads, using a programmer-specified scheduling policy. While the existing scheduling …

To improve scalability, some many-core architectures abandon global cache coherence, but
still provide a shared address space. Partitioning the shared memory and communicating …

May-Happen-in-Parallel (MHP) analysis is becoming the backbone of many of the parallel
analyses and optimizations. In this paper, we present new approaches to do MHP analysis …

OpenMP is one of the most popular APIs widely used to realize parallelism in C/C++ and
FORTRAN programs. For efficient execution, an OpenMP program internally creates a team …

We present a new optimization DECAF that optimizes recursive task parallel (RTP)
programs by reducing the task creation and termination overheads. DECAF reduces the task …

Task-parallel languages such as X10 implement dynamic lightweight task-parallel execution
model, where programmers are encouraged to express the ideal parallelism in the program …