OpenMP has been very successful in exploiting structured parallelism in applications. With
increasing application complexity, there is a growing need for addressing irregular …

This paper describes SuperMatrix, a runtime system that parallelizes matrix operations for
SMP and/or multi-core architectures. We use this system to demonstrate how code …

This paper presents a novel proposal to define task parallelism in OpenMP. Task parallelism
has been lacking in the OpenMP language for a number of years already. As we show, this …

The OpenMP standard was conceived to parallelize dense array-based applications, and it
has achieved much success with that. Recently, a novel tasking proposal to handle …

Many numerical algorithms on matrices or tensors can be formulated in a blocking style
which improves performance due to better cache locality. In imperative languages, blocking …

In LAPACK many matrix operations are cast as block algorithms which iteratively process a
panel using an unblocked algorithm and then update a remainder matrix using the high …

We show empirically that some of the issues that affected the design of linear algebra
libraries for distributed memory architectures will also likely affect such libraries for shared …

The development of high-performance numeric libraries has become extraordinarily difficult
due to multiple processor cores, vector instruction sets, and deep memory hierarchies. To …

In LAPACK many matrix operations are cast as block algorithms which iteratively process a
panel using an unblocked algorithm and then update a remainder matrix using the high …

Modern processors have multiple cores, making multiprocessing essential for competitive
desktop linear algebra. Asynchronous processing with much inherent parallelism can be …