Results 271 to 280 of about 3,076,045 (348)

Acceleration of Image Classification and Object Tracking by the Intel Neural Compute Stick 2 with Power Efficiency Evaluation on Raspberry Pi 4B. [PDF]

Sensors (Basel)
Gao T, Suto J.
europepmc   +1 more source

Parallel Lossless Compression of Raw Bayer Images on FPGA-Based High-Speed Camera. [PDF]

Sensors (Basel)
Regoršek Ž, Gorkič A, Trost A.
europepmc   +1 more source

Multiscale regional calibration network for crowd counting. [PDF]

Sci Rep
Yu J, Hu H.
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Efficient nonlinear function approximation in analog resistive crossbars for recurrent neural networks. [PDF]

Nat Commun
Yang J, Mao R, Jiang M, Cheng Y, Sun PV, Dong S, Pedretti G, Sheng X, Ignowski J, Li H, Li C, Basu A.   +11 more
europepmc   +1 more source

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Streaming Task Parallelism

Proceedings of the 29th ACM on International Conference on Supercomputing, 2015
Stream computing is often associated with regular, data-intensive applications, and more specifically with the family of cyclo-static data-flow models. The term also refers to bulk-synchronous data parallelism on SIMD architectures. Both interpretations are valid but incomplete: streams underline the formal definition of Kahn process networks, a ...
Albert Cohen
semanticscholar   +4 more sources

Isolation for nested task parallelism

Proceedings of the 2013 ACM SIGPLAN international conference on Object oriented programming systems languages & applications, 2013
Isolation--the property that a task can access shared data without interference from other tasks--is one of the most basic concerns in parallel programming. Whilethere is a large body of past work on isolated task-parallelism, the integration of isolation, task-parallelism, and nesting of tasks has been a difficult and unresolved challenge. In this pa-
Jisheng Zhao, Roberto Lublinerman, Zoran Budimlic, Swarat Chaudhuri, Vivek Sarkar   +4 more
semanticscholar   +3 more sources

Task-Parallel Programming with Constrained Parallelism

IEEE Conference on High Performance Extreme Computing, 2022
Task graph programming model (TGPM) has become central to a wide range of scientific computing applications because it enables top-down optimization of parallelism that governs the macro-scale performance.
Tsung-Wei Huang, L. Hwang
semanticscholar   +1 more source

Efficiently Supporting Dynamic Task Parallelism on Heterogeneous Cache-Coherent Systems

International Symposium on Computer Architecture, 2020
Manycore processors, with tens to hundreds of tiny cores but no hardware-based cache coherence, can offer tremendous peak throughput on highly parallel programs while being complexity and energy efficient.
Moyang Wang, T. Ta, Lin Cheng, C. Batten
semanticscholar   +1 more source

A System for Fast and Scalable Point Cloud Indexing Using Task Parallelism

Smart Tools and Applications in Graphics, 2020
We introduce a system for fast, scalable indexing of arbitrarily sized point clouds based on a task-parallel computation model. Points are sorted using Morton indices in order to efficiently distribute sets of related points onto multiple concurrent ...
P. Bormann, Michel Krämer
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GPU-based Collaborative Filtering Recommendation System using Task parallelism approach

2018 2nd International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC), 2018 2nd International Conference on, 2018
Collaborative filtering is one among the top most preferred techniques when implementing recommendation systems. In recent times, more interest has turned towards parallel GPU-based implementation of collaborative filtering algorithms.
N. Sivaramakrishnan, V. Subramaniyaswamy
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