CUDA-Lite: Reducing GPU Programming Complexity -- MCUDA: An Efficient Implementation of CUDA Kernels for Multi-core CPUs -- Automatic Pre-Fetch and Modulo Scheduling Transformations for the Cell BE Architecture -- Efficient Set Sharing Using ZBDDs -- Register Bank Assignment for Spatially Partitioned Processors -- Smashing: Folding Space to Tile through Time -- Identification of Heap–Carried Data Dependence Via Explicit Store Heap Models -- On the Scalability of an Automatically Parallelized Irregular Application -- Statistically Analyzing Execution Variance for Soft Real-Time Applications -- Minimum Lock Assignment: A Method for Exploiting Concurrency among Critical Sections -- Set-Congruence Dynamic Analysis for Thread-Level Speculation (TLS) -- Thread Safety through Partitions and Effect Agreements -- P-Ray: A Software Suite for Multi-core Architecture Characterization -- Scalable Implementation of Efficient Locality Approximation -- P-OPT: Program-Directed Optimal Cache Management -- Compiler-Driven Dependence Profiling to Guide Program Parallelization -- gluepy: A Simple Distributed Python Programming Framework for Complex Grid Environments -- A Fully Parallel LISP2 Compactor with Preservation of the Sliding Properties -- A Case Study in Tightly Coupled Multi-paradigm Parallel Programming -- ASYNC Loop Constructs for Relaxed Synchronization -- Design for Interoperability in stapl: pMatrices and Linear Algebra Algorithms -- Implementation of Sensitivity Analysis for Automatic Parallelization -- Just-In-Time Locality and Percolation for Optimizing Irregular Applications on a Manycore Architecture -- Exploring the Optimization Space of Dense Linear Algebra Kernels.