Java Threads
Integer Programming and Conway's Game of Life
SIAM Review
Evaluating derivatives: principles and techniques of algorithmic differentiation
Evaluating derivatives: principles and techniques of algorithmic differentiation
JOMP—an OpenMP-like interface for Java
Proceedings of the ACM 2000 conference on Java Grande
Concurrent Programming in Java: Design Principles and Patterns
Concurrent Programming in Java: Design Principles and Patterns
Computing in Science and Engineering
MPIJAVA: An Object-Oriented JAVA Interface to MPI
Proceedings of the 11 IPPS/SPDP'99 Workshops Held in Conjunction with the 13th International Parallel Processing Symposium and 10th Symposium on Parallel and Distributed Processing
MPJ: A Proposed Java Message Passing API and Environment for High Performance Computing
IPDPS '00 Proceedings of the 15 IPDPS 2000 Workshops on Parallel and Distributed Processing
NINJA: Java for high performance numerical computing
Scientific Programming
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Parallel programming of high-performance computers has emerged as a key technology for the numerical solution of large-scale problems arising in computational science and engineering (CSE). The authors believe that principles and techniques of parallel programming are among the essential ingredients of any CSE as well as computer science curriculum. Today, opinions on the role and importance of parallel programming are diverse. Rather than seeing it as a marginal beneficial skill optionally taught at the graduate level, we understand parallel programming as crucial basic skill that should be taught as an integral part of the undergraduate computer science curriculum. A practical training course developed for computer science undergraduates at Aachen University is described. Its goal is to introduce young computer science students to different parallel programming paradigms for shared and distributed memory computers as well as to give a first exposition to the field of computational science by simple, yet carefully chosen sample problems.