Languages, Compilers, and Run-Time Systems for Scalable Computers, 2000 5th International Workshop, LCR 2000 Rochester, NY, USA, May 25-27, 2000 Selected Papers Lecture Notes in Computer Science Series, Vol. 1915

The papers in this volume are organized in topical sections on data-intensive computing, static analysis, openMP support, synchronization, software DSM, heterogeneous/-meta-computing, issues of load, and compiler-supported parallelism.

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.