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Data parallelism
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41	TOWARDS GPU HEVC INTRA DECODING: SEIZING FINE-GRAIN PARALLELISM Diego F. de Souza, Aleksandar Ilic, Nuno Roma, Leonel Sousa INESC-ID, IST, Universidade de Lisboa Rua Alves Redol 9, Lisboa, Portugal {diego.souza, Add to Reading List Source URL: www.inesc-id.pt Language: English - Date: 2016-03-10 05:53:57 Computing Video compression Data compression Video ISO standards Videotelephony MPEG Computer file formats High Efficiency Video Coding Coding tree unit Deblocking filter Graphics processing unit
42	Lock-free programming for the masses KC Sivaramakrishnan University of Cambridge Efficient concurrent programming libraries are essential for taking advantage of fine-grained parallelism on multicore hardware. We present Add to Reading List Source URL: kcsrk.info Language: English - Date: 2016-08-01 08:25:07 Concurrency control Computing Software engineering Computer programming Transaction processing Software design patterns Functional languages Data management Software transactional memory Treiber Stack Lock OCaml
43	Performance Enhancement with Speculative Execution Based Parallelism for Processing Large-scale XML-based Application Data Michael R. Head Add to Reading List Source URL: www.cs.binghamton.edu Language: English - Date: 2009-04-08 20:31:37 Finite automata Compiler construction Parallel computing Analysis of parallel algorithms Speedup VTD-XML Concurrent data structure Finite-state machine Regular expression Deterministic finite automaton Parsing XML schema
44	Eﬀective Concurrency with Algebraic Eﬀects Stephen Dolan1, Leo White2, KC Sivaramakrishnan1, Jeremy Yallop1, Anil Madhavapeddy1 1 Add to Reading List Source URL: kcsrk.info Language: English - Date: 2016-08-01 08:25:07 Parallel computing Functional languages Concurrent programming languages Scala Haskell Concurrent computing Data parallelism Parallelism Scheduling
45	New Abstractions for Data Parallel Programming James C. Brodman, Basilio B. Fraguela† , Mar´ıa J. Garzar´an, and David Padua Department of Computer Science University of Illinois at Urbana-Champaign brodman2, garzar Add to Reading List Source URL: polaris.cs.uiuc.edu Language: English - Date: 2009-03-05 10:59:40 Parallel computing Fortran ILLIAC IV APL Vector processor Data parallelism Array data type Bit array Cilk General-purpose computing on graphics processing units Array data structure NESL
46	PDF Document Add to Reading List Source URL: www.inesc-id.pt Language: English - Date: 2011-07-21 16:55:12 Parallel computing Multi-core processor Distributed computing Algorithm Parallel algorithm Scalable parallelism Data-intensive computing
47	Parallel Processing Functional Programming and Parallel Computing Multicore processors are becoming commonplace They typically consist of several processors, and a shared memory: Add to Reading List Source URL: www.idt.mdh.se Language: English - Date: 2013-12-03 05:18:36 Parallel computing Task parallelism Data parallelism GNU parallel ALGOL 68 Functional programming Parallelism Thread Maths24
48	Programming for Parallelism and Locality with Hierarchically Tiled Arrays Gheorghe Almasi† , Add to Reading List Source URL: polaris.cs.uiuc.edu Language: English - Date: 2006-03-20 17:33:54 Parallel computing Array programming languages HTML Application MATLAB Array programming Fortran Array data type Array data structure Data parallelism Task parallelism ZPL
49	Functional Programming and Parallel Computing Björn Lisper School of Innovation, Design, and Engineering Mälardalen University http://www.idt.mdh.se/˜blr/ Add to Reading List Source URL: www.idt.mdh.se Language: English - Date: 2013-12-03 05:18:34 Parallel computing Thread Multi-core processor Data parallelism Functional programming Central processing unit Algorithmic skeleton Concurrent computing
50	DOC Document Add to Reading List Source URL: www.capsl.udel.edu Language: English - Date: 2015-02-12 15:30:49 Parallel computing Guang Gao Computer architecture Software pipelining Symposium on Parallelism in Algorithms and Architectures Superscalar processor Dataflow architecture Instruction-level parallelism Data-intensive computing XPL Rock Josh Fisher

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