Languages, Compilers, and Run-Time Systems for Scalable Computers 5th International Workshop, LCR 2000 Rochester, NY, USA, May 25-27, 2000 Selected Papers
| Other Authors: | |
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| Format: | eBook |
| Language: | English |
| Published: |
Berlin, Heidelberg
Springer Berlin Heidelberg
2000, 2000
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| Edition: | 1st ed. 2000 |
| Series: | Lecture Notes in Computer Science
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| Subjects: | |
| 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