1,184 papers · page 57 of 60
Large-scale shared memory multiprocessors typically support a multilevel memory hierarchy consisting of per-processor caches, a local portion of shared memory, and remote shared memory. On such machines, the performance of parallel programs is often limited by the high latency of…
article High performance Fortran without templates: an alternative model for distribution and alignment. Share on Authors: Barbara M. Chapman View Profile , Piyush Mehrotra View Profile , Hans P. Zima View Profile Authors Info & Claims ACM SIGPLAN NoticesVolume 28Issue 7July 1993…
Generating local addresses and communication sets is an important issue in distributed-memory implementations of data-parallel languages such as High Performance Fortran. We show that for an array A affinely aligned to a template that is distributed across p processors with a cyc…
A vast body of theoretical research has focused either on overly simplistic models of parallel computation, notably the PRAM, or overly specific models that have few representatives in the real world. Both kinds of models encourage exploitation of formal loopholes, rather than re…
We present a solution to the reaching definitions problem for programs with explicit lexically specified parallel constructs, such as cobegin/coend or parallel_sections, both with and without explicit synchronization operations, such as Post, Wait or Advance. The reaching definit…
The ParaScope Editor is an interactive parallel programming tool that assists knowledgeable users in developing scientific Fortran programs. It displays the results of sophisticated program analyses, provides a set of powerful interactive transformations, and supports program edi…
We describe computation migration, a new technique that is based on compile-time program transformations, for accesing remote data in a distributed-memory parallel system. In contrast with RPC-style access, where the access is performed remotely, and with data migration, where th…
This paper describes the design and implementation of a concurrent compacting garbage collector for languages that distinguish mutable data from immutable data (e.g., ML) as well for languages that manipulate only immutable data (e.g., pure functional languages such as Haskell). …
Parallel programs frequently use barriers to synchronize successive steps in an algorithm. In the presence of multiprogramming the choice of spinning versus blocking barriers can have a significant impact on performance. We demonstrate how competitive spinning techniques previous…
This paper discusses some of the issues involved in implementing a shared-address space programming model on large-scale, distributed-memory multiprocessors. While such a programming model can be implemented on both shared-memory and message-passing architectures, we argue that t…
When the inter-iteration dependency pattern of the iterations of a loop cannot be determined statically, compile time parallelization of the loop is not possible. In these cases, runtime parallelization [8] is the only alternative. The idea is to transform the loop into two code …
Non-concurrency analysis is a set of techniques for statically identifying pairs (or sets) of statements in a concurrent program which can never happen together. This information aids programmers in debugging and manually optimizing programs, improves the precision of data flow a…
We have built a portable platform for running Standard ML of New Jersey programs on multiprocessors. It can be used to implement user-level thread packages for multiprocessors within the ML language with first-class continuations. The platform supports experimentation with differ…
Efficient parallel execution of a high-level data-parallel language based on nested sequences, higher order functions and generalized iterators can be realized in the vector model using a suitable representation of nested sequences and a small set of transformational rules to dis…
Data-parallelism provides a clean conceptual framework for parallel programming. We are developing two programming languages: a high level equational language, called EL*, and a low-level implementation language. Both languages exploit data-parallelism instead of control-parallel…
The effective management of caches is critical to the performance of applications on shared-memory multiprocessors. In this paper, we discuss a technique for software cache coherence tht is based upon the integration of a program-level abstraction for shared data with software ca…
The process of instrumenting a program to study its behavior can lead to perturbations in the program's execution. These perturbations can become severe for large parallel systems or problem sizes, even when one captures only high level events. In this paper, we address the impor…
||MAPLE|| (speak: parallel Maple) is a portable system for parallel symbolic computation. The system is built as an interface between the parallel declarative programming language Strand and the sequential computer algebra system Maple, thus providing the elegance of Strand and t…
For many applications, achieving good performance on a private memory parallel computer requires exploiting data parallelism as well as task parallelism. Depending on the size of the input data set and the number of nodes (i.e., processors), different tradeoffs between task and d…
Several novel techniques for efficient implementtion of concurrent object-oriented languages on general purpose, stock multicomputers are presented. These techniques have been developed in implementing our concurrent object-oriented language ABCL on a Fujitsu Laboratory's experim…