BSP Functional Programming: Examples of a Cost Based Methodology

Abstract. Bulk-Synchronous Parallel ML (BSML) is a functional data-parallel language for the implementation of Bulk-Synchronous Parallel (BSP) algorithms. It makes an estimation of the execution time (cost) possible. This paper presents some general examples of BSML programs and a comparison of their predicted costs with the measured execution time on a parallel machine

Identifying A Unifying Mechanism for the Implementation of Concurrency Abstractions on Multi-Language Virtual Machines

Supporting all known abstractions for concurrent and parallel programming in a virtual machines (VM) is a futile undertaking, but it is required to give programmers appropriate tools and performance. Instead of supporting all abstractions directly, VMs need a unifying mechanism similar to \textttINVOKEDYNAMIC for JVMs. Our survey of parallel and concurrent programming concepts identifies concurrency abstractions as the ones benefiting most from support in a VM. Currently, their semantics is often weakened, reducing their engineering benefits. They require a mechanism to define flexible language guarantees. Based on this survey, we define an ownership-based meta-object protocol as candidate for VM support. We demonstrate its expressiveness by implementing actor semantics, software transactional memory, agents, CSP, and active objects. While the performance of our prototype confirms the need for VM support, it also shows that the chosen mechanism is appropriate to express a wide range of concurrency abstractions in a unified way

Parallel computing in information retrieval - An updated review

The progress of parallel computing in Information Retrieval (IR) is reviewed. In particular we stress the importance of the motivation in using parallel computing for Text Retrieval. We analyse parallel IR systems using a classification due to Rasmussen [1] and describe some parallel IR systems. We give a description of the retrieval models used in parallel Information Processing.. We describe areas of research which we believe are needed

Parallelization with Tree Skeletons

Trees are useful data structures, but to design efficient parallel programs over trees is known to be more difficult than to do over lists. Although several important..

Examining the Expert Gap in Parallel Programming

Abstract. Parallel programming is often regarded as one of the hardest programming disciplines. On the one hand, parallel programs are notoriously prone to concurrency errors; and, while trying to avoid such errors, achieving program performance becomes a significant challenge. As a result of the multicore revolution, parallel programming has however ceased to be a task for domain experts only. And for this reason, a large variety of languages and libraries have been proposed that promise to ease this task. This paper presents a study to investigate whether such approaches succeed in closing the gap between domain experts and mainstream developers. Four approaches are studied: Chapel, Cilk, Go, and Threading Building Blocks (TBB). Each approach is used to implement a suite of benchmark programs, which are then reviewed by notable experts in the language. By comparing original and revised versions with respect to source code size, coding time, execution time, and speedup, we gain insights into the importance of expert knowledge when using modern parallel programming approaches.