Languages and Compilers for Parallel Computing

Code and Data Transformations An Affine Scheduling Framework for Integrating Data Layout and Loop Transformations.- Guiding Code Optimizations with Deep Learning-Based Code Matching.- Expanding Opportunities for Array Privatization in Sparse Computations.- OpenMP and Fortran Concurrent Execution of Deferred OpenMP Target Tasks with Hidden Helper Threads.- Using Hardware Transactional Memory to Implement Speculative Privatization in OpenMP.- Improving Fortran Performance Portability.- Domain Specific Compilation COMET: A Domain-Specic Compilation of High-Performance Computational Chemistry.- G-Code Re-compilation and Optimization for Faster 3D Printing.- Li Machine Language and Quantum Computing Optimized Code Generation for Deep Neural Networks.- Thermal-Aware Compilation of Spiking Neural Networks to Neuromorphic Hardware.- A Quantum-Inspired Model For Bit-Serial SIMD-Parallel Computation.- Performance Analysis Enhancing the Top-Down Microarchitectural Analysis Method Using Purchasing Power Parity Theory.- Code Generation Cain: Automatic Code Generation for Simultaneous Convolutional Kernels on Focal-plane Sensor-processors.- Reordering Under the ECMAScript Memory Consistency Model.- Verication of Vectorization of Signal Transforms.