Languages, Compilers, and Run-Time Systems for Scalable Computers 5th International Workshop, LCR 2000 Rochester, NY, USA, May 25-27, 2000 Selected Papers

Bibliographic Details
Other Authors: Dwarkadas, Sandhya (Editor)
Format: eBook
Published: Berlin, Heidelberg Springer Berlin Heidelberg 2000, 2000
Edition:1st ed. 2000
Series:Lecture Notes in Computer Science
Online Access:
Collection: Springer Book Archives -2004 - Collection details see MPG.ReNa
Table of Contents:
  • I/O, Data-Intensive Computing
  • A Collective I/O Scheme Based on Compiler Analysis
  • Achieving Robust, Scalable Cluster I/O in Java
  • High Level Programming Methodologies for Data Intensive Computations
  • Static Analysis
  • Static Analysis for Guarded Code
  • A Framework for Efficient Register Allocation through Selective Register Demotion
  • A Comparison of Locality Transformations for Irregular Codes
  • OpenMP Support
  • UPMLIB: A Runtime System for Tuning the Memory Performance of OpenMP Programs on Scalable Shared-Memory Multiprocessors
  • Performance Evaluation of OpenMP Applications with Nested Parallelism
  • Adaptive Parallelism for OpenMP Task Parallel Programs
  • Synchronization
  • Optimizing Mutual Exclusion Synchronization in Explicitly Parallel Programs
  • Detecting Read-Only Methods in Java
  • Software DSM
  • The Effect of Contention on the Scalability of Page-Based Software Shared Memory Systems
  • Measuring Consistency Costs for Distributed Shared Data
  • Compilation and Runtime Optimizations for Software Distributed Shared Memory
  • Heterogeneous/Meta-Computing
  • Run-Time Support for Distributed Sharing in Typed Languages
  • InterWeave: A Middleware System for Distributed Shared State
  • Run-Time Support for Adaptive Heavyweight Services
  • An Infrastructure for Monitoring and Management in Computational Grids
  • Issues of Load
  • Realistic CPU Workloads through Host Load Trace Playback
  • Thread Migration and Load Balancing in Heterogeneous Environments
  • Compiler-Supported Parallelism
  • Toward Compiler Support for Scalable Parallelism Using Multipartitioning
  • Speculative Parallelization of Partially Parallel Loops