Combined Iterative and Model-driven Optimization in an Automatic Parallelization Framework
Proceedings of the 2010 ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis
Using machine learning to improve automatic vectorization
ACM Transactions on Architecture and Code Optimization (TACO) - HIPEAC Papers
Predictive modeling in a polyhedral optimization space
CGO '11 Proceedings of the 9th Annual IEEE/ACM International Symposium on Code Generation and Optimization
Vapor SIMD: Auto-vectorize once, run everywhere
CGO '11 Proceedings of the 9th Annual IEEE/ACM International Symposium on Code Generation and Optimization
Polyhedral parallel code generation for CUDA
ACM Transactions on Architecture and Code Optimization (TACO) - Special Issue on High-Performance Embedded Architectures and Compilers
Polyhedral-based data reuse optimization for configurable computing
Proceedings of the ACM/SIGDA international symposium on Field programmable gate arrays
When polyhedral transformations meet SIMD code generation
Proceedings of the 34th ACM SIGPLAN conference on Programming language design and implementation
Semantics-preserving data layout transformations for improved vectorisation
Proceedings of the 2nd ACM SIGPLAN workshop on Functional high-performance computing
Hybrid type legalization for a sparse SIMD instruction set
ACM Transactions on Architecture and Code Optimization (TACO)
Breaking SIMD shackles with an exposed flexible microarchitecture and the access execute PDG
PACT '13 Proceedings of the 22nd international conference on Parallel architectures and compilation techniques
Compiling Scilab to high performance embedded multicore systems
Microprocessors & Microsystems
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Transactional memory is being advanced as an alternative to traditional lock-based synchronization for concurrent programming. Transactional memory simplifies the programming model and maximizes concurrency. At the same time, transactions can suffer ...