Languages and Compilers for Parallel Computing

A Communication Framework for Fault-Tolerant Parallel Execution.- The STAPL pList.- Hardware Support for OpenMP Collective Operations.- Loop Transformation Recipes for Code Generation and Auto-Tuning.- MIMD Interpretation on a GPU.- TL-DAE: Thread-Level Decoupled Access/Execution for OpenMP on the Cyclops-64 Many-Core Processor.- Mapping Streaming Languages to General Purpose Processors through Vectorization.- A Balanced Approach to Application Performance Tuning.- Automatically Tuning Parallel and Parallelized Programs.- DFT Performance Prediction in FFTW.- Safe and Familiar Multi-core Programming by Means of a Hybrid Functional and Imperative Language.- Hierarchical Place Trees: A Portable Abstraction for Task Parallelism and Data Movement.- OSCAR API for Real-Time Low-Power Multicores and Its Performance on Multicores and SMP Servers.- Programming with Intervals.- Adaptive and Speculative Memory Consistency Support for Multi-core Architectures with On-Chip Local Memories.- Synchronization-Free Automatic Parallelization: Beyond Affine Iteration-Space Slicing.- Automatic Data Distribution for Improving Data Locality on the Cell BE Architecture.- Automatic Restructuring of Linked Data Structures.- Using the Meeting Graph Framework to Minimise Kernel Loop Unrolling for Scheduled Loops.- Efficient Tiled Loop Generation: D-Tiling.- Effective Source-to-Source Outlining to Support Whole Program Empirical Optimization.- Speculative Optimizations for Parallel Programs on Multicores.- Fastpath Speculative Parallelization.- PSnAP: Accurate Synthetic Address Streams through Memory Profiles.- Enforcing Textual Alignment of Collectives Using Dynamic Checks.- A Code Generation Approach for Auto-Vectorization in the Spade Compiler.- Portable Just-in-Time Specialization of Dynamically Typed Scripting Languages.- Reducing Training Time in a One-Shot Machine Learning-Based Compiler.- Optimizing Local Memory Allocation and Assignment through a Decoupled Approach.- Unrolling Loops