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OpenMDSP: Extending OpenMP to Program Multi-Core DSP

by Jiangzhou He, Wenguang Chen, Guangri Chen, Weimin Zheng, Zhizhong Tang, Ong Ye
"... Abstract—Multi-core Digital Signal Processors (DSP) are widely used in wireless telecommunication, core network transcoding, industrial control, and audio/video processing etc. Comparing with general purpose multi-processors, the multicore DSPs normally have more complex memory hierarchy, such as on ..."
Abstract - Cited by 2 (0 self) - Add to MetaCart
, such as on-chip core-local memory and non-cache-coherent shared memory. As a result, it is very challenging to write efficient multi-core DSP applications. The current approach to program multi-core DSPs is based on proprietary vendor SDKs, which only provides low-level, non-portable primitives. While

Multi-core Implementations of the Concurrent Collections Programming Model

by Aparna Ch, Kathleen Knobe, Geoff Lowney, Vivek Sarkar, Leo Treggiari
"... Abstract. In this paper we introduce the Concurrent Collections pro-gramming model, which builds on past work on TStreams [8]. In this model, programs are written in terms of high-level application-specific operations. These operations are partially ordered according to only their semantic constrain ..."
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Abstract. In this paper we introduce the Concurrent Collections pro-gramming model, which builds on past work on TStreams [8]. In this model, programs are written in terms of high-level application-specific operations. These operations are partially ordered according to only their semantic

Exploiting coarse-grained task, data, and pipeline parallelism in stream programs,

by Michael I Gordon , William Thies , Saman Amarasinghe - Proceedings of the 12th International Conference on Architectural Support for Programming Languages and Operating Systems, ASPLOS-XII, , 2006
"... Abstract As multicore architectures enter the mainstream, there is a pressing demand for high-level programming models that can effectively map to them. Stream programming offers an attractive way to expose coarse-grained parallelism, as streaming applications (image, video, DSP, etc.) are naturall ..."
Abstract - Cited by 133 (6 self) - Add to MetaCart
Abstract As multicore architectures enter the mainstream, there is a pressing demand for high-level programming models that can effectively map to them. Stream programming offers an attractive way to expose coarse-grained parallelism, as streaming applications (image, video, DSP, etc

Research Article A Parallelized Implementation of Turbo Decoding Based on Network on Chip Multi-core Processor

by Chaolong Zhang, Zhekun Hu, Jie Chen , 2014
"... With the evolution of wireless communication systems, it is increasingly difficult for Application Specific Integrated Circuit (ASIC) solutions to meet the daily changing requirements. A network on chip (NOC) multi-core processor based on message-passing programming model is designed to implement th ..."
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With the evolution of wireless communication systems, it is increasingly difficult for Application Specific Integrated Circuit (ASIC) solutions to meet the daily changing requirements. A network on chip (NOC) multi-core processor based on message-passing programming model is designed to implement

Using Analytical Models to Efficiently Explore Hardware Transactional Memory and Multi-core Co-design

by James Poe, Chang-burm Cho, Tao Li - In Proc. of International Symposium on Computer Architecture and High Performance Computing , 2008
"... Transactional memory is emerging as a parallel programming paradigm for multi-core processors. Despite the recent interest in transactional memory, there has been no study to characterize the interaction between hardware transactional memory (HTM) design dimensions and multi-core microarchitecture c ..."
Abstract - Cited by 4 (3 self) - Add to MetaCart
configuration. In this paper, we investigate the use of analytical modeling techniques to build application-specific performance models for understanding the interaction between HTM and multi-core configurations across large design points and for efficiently exploring the co-design space between the two. A key

The design and implementation Ocelot’s dynamic binary translator from PTX to multi-core x86

by Gregory Diamos , 2009
"... Abstract—Ocelot is a dynamic compilation framework designed to map the explicitly parallel PTX execution model used by NVIDIA CUDA applications onto diverse many-core architectures. Ocelot includes a dynamic binary translator from PTX to many-core processors that leverages the LLVM code generator to ..."
Abstract - Cited by 8 (1 self) - Add to MetaCart
Abstract—Ocelot is a dynamic compilation framework designed to map the explicitly parallel PTX execution model used by NVIDIA CUDA applications onto diverse many-core architectures. Ocelot includes a dynamic binary translator from PTX to many-core processors that leverages the LLVM code generator

Author manuscript, published in "Pespma 2010- Workshop on Parallel Execution of Sequential Programs on Multi-core Architecture (2010)" Energy Efficiency via the N-way Model

by Romain Cledat, Santosh Pande , 2010
"... With core counts as well as heterogeneity on the rise, the sequential components of applications are becoming the major bottleneck in performance scaling as predicted by Amdahl’s law. We are therefore faced with the simultaneous problems of occupying an increasing number of cores and improving seque ..."
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sequential performance. In this work, we specifically focus on improving the energy efficiency of sequential algorithms through the n-way programming model. In previous work, we introduced the n-way programming model which seeks to exploit the algorithmic diversity present in certain computations in order

A Performance Study of General-Purpose Applications on Graphics Processors Using CUDA

by Shuai Che, Michael Boyer, Jiayuan Meng, David Tarjan, Jeremy W. Sheaffer, Kevin Skadron
"... Graphics processors (GPUs) provide a vast number of simple, data-parallel, deeply multithreaded cores and high memory bandwidths. GPU architectures are becoming increasingly programmable, offering the potential for dramatic speedups for a variety of generalpurpose applications compared to contempora ..."
Abstract - Cited by 86 (7 self) - Add to MetaCart
on the GPU. GPU performance is compared to both single-core and multicore CPU performance, with multicore CPU implementations written using OpenMP. The paper also discusses advantages and inefficiencies of the CUDA programming model and some desirable features that might allow for greater ease of use

Natively supporting true one-sided communication in MPI on multi-core systems with InfiniBand

by G. Santhanaraman, P. Balaji, K. Gopalakrishnan, R. Thakur - in Proceedings of the 9th International Symposium of Cluster Computing and the Grid (CCGrid), 2009
"... As high-end computing systems continue to grow in scale, the per-formance that applications can achieve on such large scale systems depends heavily on their ability to avoid explicitly synchronized communication with other processes in the system. Accordingly, several modern and legacy parallel prog ..."
Abstract - Cited by 3 (1 self) - Add to MetaCart
-speed networks such as InfiniBand (IB) to allow for true one-sided communication in MPI. In this paper, we extend this work to natively take advantage of one-sided atomic operations on cache-coherent multi-core/multi-processor architec-tures while still utilizing the benefits of networks such as IB. Specif

Parallel Consistency in Constraint Programming

by Carl Christian Rolf, Krzysztof Kuchcinski
"... Program parallelization becomes increasingly important when new multi-core architectures provide ways to improve performance. One of the greatest challenges of this development lies in programming parallel applications. Using declarative languages, such as constraint programming, can make the tran ..."
Abstract - Cited by 3 (3 self) - Add to MetaCart
Program parallelization becomes increasingly important when new multi-core architectures provide ways to improve performance. One of the greatest challenges of this development lies in programming parallel applications. Using declarative languages, such as constraint programming, can make
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