Streaming APIs are becoming more pervasive in mainstream Object-Oriented programming
languages and platforms. For example, the Stream API introduced in Java 8 allows for …

Compilation techniques for nested-parallel applications that can adapt to hardware and
dataset characteristics are vital for unlocking the power of modern hardware. This paper …

Tiling is a key technique to reduce data movement in matrix computations. While tiling is well
understood and widely used for dense matrix/tensor computations, effective tiling of sparse …

This paper describes the design and implementation of a suit of static analyses and code
generation techniques to annotate programs with OpenMP pragmas for task parallelism …

This work focuses on accelerating the multiplication of a dense random matrix with a (fixed)
sparse matrix, which is frequently used in sketching algorithms. We develop a novel scheme …

This work focuses on accelerating the multiplication of a dense random matrix with a (fixed)
sparse matrix, which is frequently used in sketching algorithms. We develop a novel scheme …

We then will turn our attention to legacy-sequential code written in programming languages
such as C. In this context we study dependence analysis, as a tool for reasoning about loop …

Sparse matrix and tensor computations are challenging to optimize. In contrast to dense
matrix/tensor computations, the pattern of data access is typically irregular for sparse …

We study the feasibility and performance efficiency of expressing a complex financial
numerical algorithm with high-level functional parallel constructs. The algorithm we …

This paper presents TaskMiner, a tool that automatically finds task parallelism in C code.
TaskMiner solves classic problems of irregular parallelism, such as finding the memory …