Partitioned Global Address Space (PGAS) languages are convenient for expressing
algorithms with large, random-access data, and they have proven to provide high …

We present Sequoia, a programming language designed to facilitate the development of
memory hierarchy aware parallel programs that remain portable across modern machines …

In this paper, we address the question of how to automatically map computational kernels to
highly efficient code for a wide range of computing platforms and establish the correctness of …

The cost of data movement has always been an important concern in high performance
computing (HPC) systems. It has now become the dominant factor in terms of both energy …

We now have 20 years of data under our belt about the performance of supercomputers
against at least a single floating-point benchmark from dense linear algebra. Until about …

UPC++ is a C++ library that supports high-performance computation via an asynchronous
communication framework. This paper describes a new incarnation that differs substantially …

Exploiting data locality in GPUs is critical to making more efficient use of the existing caches
and the NUMA-based memory hierarchy expected in future GPUs. While modern GPU …

DARPA's Ubiquitous High-Performance Computing (UHPC) program asked researchers to
develop computing systems capable of achieving energy efficiencies of 50 GOPS/Watt …

Stream based languages are a popular approach to expressing parallelism in modern
applications. The efficient map** of streaming parallelism to multi-core processors is …

Modern computer systems feature multiple homogeneous or heterogeneous computing
units with deep memory hierarchies, and expect a high degree of thread-level parallelism …