Towards Massively Parallel Computations in Algebraic Geometry

Verifying Massively Data Parallel Multi-Stage Computations

Data parallel, multi-stage computations occurring on a massive scale are difficult to verify. With the recent advent of various parallel computing platforms [2, 4], and the resultant increased availability and accessibility of significant computational resources at a relatively economical price, more and more users are going to take advantage of the computational resources offered by the cloud ...

Basic Sparse Matrix Computations on Massively Parallel Computers ∗

This paper presents a preliminary experimental study of the performance of basic sparse matrix computations on the CM-200 and the CM-5. We concentrate on examining various ways of performing general sparse matrix-vector operations and the basic primitives on which these are based. We compare various data structures for storing sparse matrices and their corresponding matrix – vector operations. ...

A massively parallel tensor contraction framework for coupled-cluster computations

Precise calculation of molecular electronic wavefunctions by methods such as coupled-cluster requires the computation of tensor contractions, the cost of which has polynomial computational scaling with respect to the system and basis set sizes. Each contraction may be executed via matrix multiplication on a properly ordered and structured tensor. However, data transpositions are often needed to...

Massively parallel fault tolerant computations on syntactical patterns

Structured Data Access Annotations for Massively Parallel Computations

We describe an approach aimed at addressing the issue of joint exploitation of control (stream) and data parallelism in a skeleton based parallel programming environment, based on annotations and refactoring. Annotations drive efficient implementation of a parallel computation. Refactoring is used to transform the associated skeleton tree into a more efficient, functionally equivalent skeleton ...