Languages and Compilers for Parallel Computing: 19th International Workshop, Lcpc 2006, New Orleans, La, Usa, November 2-4, 2006, Revised Papers (Paperback, 2007)

Keynote I.- Compilation Techniques for Partitioned Global Address Space Languages.- Session 1: Programming Models.- Can Transactions Enhance Parallel Programs?.- Design and Use of htalib - A Library for Hierarchically Tiled Arrays.- SP@CE - An SP-Based Programming Model for Consumer Electronics Streaming Applications.- Session 2: Code Generation.- Data Pipeline Optimization for Shared Memory Multiple-SIMD Architecture.- Dependence-Based Code Generation for a CELL Processor.- Expression and Loop Libraries for High-Performance Code Synthesis.- Applying Code Specialization to FFT Libraries for Integral Parameters.- Session 3: Parallelism.- A Characterization of Shared Data Access Patterns in UPC Programs.- Exploiting Speculative Thread-Level Parallelism in Data Compression Applications.- On Control Signals for Multi-Dimensional Time.- Keynote II.- The Berkeley View: A New Framework and a New Platform for Parallel Research.- Session 4: Compilation Techniques.- An Effective Heuristic for Simple Offset Assignment with Variable Coalescing.- Iterative Compilation with Kernel Exploration.- Quantifying Uncertainty in Points-To Relations.- Session 5: Data Structures.- Cache Behavior Modelling for Codes Involving Banded Matrices.- Tree-Traversal Orientation Analysis.- UTS: An Unbalanced Tree Search Benchmark.- Session 6: Register Allocation.- Copy Propagation Optimizations for VLIW DSP Processors with Distributed Register Files.- Optimal Bitwise Register Allocation Using Integer Linear Programming.- Register Allocation: What Does the NP-Completeness Proof of Chaitin et al. Really Prove? Or Revisiting Register Allocation: Why and How.- Session 7: Memory Management.- Custom Memory Allocation for Free.- Optimizing the Use of Static Buffers for DMA on a CELL Chip.- Runtime Address Space Computation for SDSM Systems.- A Static Heap Analysis for Shape and Connectivity: Unified Memory Analysis: The Base Framework.