shared-memory parallel programming model
OVERVIEW OF MULTICORE, PARALLEL COMPUTING, AND DATA MINING
... access data in a diff. Long transmission time.. PARALLEL PROGRAMMING MODEL. Shared-Memory Programming model[r] ...
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PARALLEL COMPUTING IMPLEMENTATION USING GPU
... global memory access: parallel loop-swap and matrix transpose techniques for regular applications, and loop collapsing for irregular ...easier programming model for general computing on ...
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Region based techniques for modeling and enhancing cluster OpenMP performance
... share memory programming model, such as OpenMP that utilizes a fork-join like parallelism approach, limits the need of data commu- nication between threads to well defined consistency points ...of ...
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Analysis of Memory Performance and Execution Models for Large-Scale Manycores.
... efficient parallel application, but it is not trivial to ...pattern, memory footprint, intra-node bandwidth, inter-node bandwidth and load distribution, a coarse domain decomposition at the process level ...
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Performance Analysis of Multilevel Parallel Applications on Shared Memory Architectures
... OpenMP parallel regions and work-sharing constructs are also ...this programming model, the code regions that correspond to the body of the parallel re- gions/loops are outlined by the ...
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Exploiting Multi Core Architectures for Process Speed Up
... C programming language on LINUX ...a shared memory programming model where parallelism takes the form of parallel function invocations by threads which can access shared ...
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AN EVOLUTIONARY APPROACH TO PARALLEL COMPUTING USING GPU
... Share memory programming is an Application Program Interface (API), jointly defined by a group of major computer hardware and software ...scalable model for developers of shared memory ...
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Programming Models for Parallel Heterogeneous Computing
... the programming model for GPU comput- ing, we build a prototype that solved the NQueens puzzle for large board sizes on GPU compute ...CUDA programming model relies on SPMD ker- nels that work ...
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OpenCL for programming shared memory multicore CPUs
... are shared memory ...plication programming interface for multi-threading computationally intensive data and task parallel ...fork/join model, which exist throughout execution of the ...
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Making State Explicit for Imperative Big Data Processing
... a shared-memory abstrac- ...vertex-centric programming model whereas SDGs target generic stateful ...for parallel processing of large datasets on clus- ...
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Parallel Computing and Multicore 2008: Tutorial
... Parallel Software Paradigms III: Component Parallel and Program Parallel continued • In a single virtual machine as in single shared memory machine with possible multi-core chips, standa[r] ...
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Relations Between Several Parallel Computational Models
... random-access memory. The pro- cessors execute the instructions of a parallel algorithm ...The shared memory stores intermediate data and results, and also serves as communication medium for ...
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Tuning a Parallel Database Algorithm on a Shared-memory Multiprocessor
... to memory to cache to disk plus process-to-process data exchange of almost all data), the bus bandwidth of 53 MB/s was used to 7 × 100 MB/83·66 s/53 MB/s = 15·8 per cent by actual and necessary data transfer, with ...
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Analyzing CUDA Workloads UsingaDetailedGPUSimulator
... flexible programming models that understanding their performance can provide insight in designing tomorrow’s manycore processors, whether those are GPUs or other- ...among memory, data, and thread level ...
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An Efficient Parallel Substrate for Typed Feature Structures on Shared Memory Parallel Machines
... An Efficient Parallel Substrate for Typed Feature Structures on Shared Memory Parallel Machines A n E f f i c i e n t P a r a l l e l S u b s t r a t e for T y p e d F e a t u r e S t r u c t u r e s[.] ...
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Parallelization of formal concept analysis algorithms
... Old and Priss have highlighted the need of developing algorithms that can handle large contexts (Old & Priss, 2004). There is no formal definition of what a large context is, however based on recent benchmarks a ...
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LIBMF: A Library for Parallel Matrix Factorization in Shared-memory Systems
... A special case of BMF is one-class matrix factorization (OCMF) in which the training matrix is still binary but contains only positive entries. OCMF is worthy to be considered as in some online activities (e.g., Pan et ...
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High Performance Computing in Java and the Cloud
... JCublas . c u b l a s A l l o c ( nn , S i z e o f . DOUBLE, d_A ) ; JCublas . c u b l a s A l l o c ( nn , S i z e o f . DOUBLE, d_B ) ; JCublas . c u b l a s A l l o c ( nn , S i z e o f . DOUBLE, d_C ) ; / / Copy t h ...
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SHARED HASH TABLES IN PARALLEL MODEL CHECKING
... Scalable explicit exploration is a good starting point for future work on multi-core X. X {(weak) LTL model checking, symbolic exploration, space-efficient explicit exploration}[r] ...
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Modeling of Communication Complexity in Parallel Computing
... Abstract: Parallel principles are the most effective way how to increase parallel computer performance and parallel algorithms (PA) ...too. Parallel using of more computing nodes (processors, ...
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