Results 201 to 210 of about 21,831,698 (267)

Parallel DEPSO-Scout: Data Parallelism

2018 International Electrical Engineering Congress (iEECON), 2018
DEPSO-Scout is a hybrid optimization algorithm combining Differential Evolution (DE), Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC). The solution convergence is balanced between exploration of PSO and exploitation from DE. The suboptimal solution has reduced by the scout bee property of ABC.
Prasitchai Boonserm, Suchada Sitjongsataporn   +1 more
openaire   +1 more source

Data parallelism in logic programming [PDF]

, 1991
Many researchers have been trying to use the implicit parallelism of logic languages parallelizing the execution of independent clauses. However this approach has the disadvantage of requiring a heavy overhead for processes scheduling and synchronizing, for data migration and for collecting the results. In this paper it is proposed a different approach,
Succi G, Marino G
openaire   +1 more source

SDP4Bit: Toward 4-bit Communication Quantization in Sharded Data Parallelism for LLM Training

Neural Information Processing Systems
Recent years have witnessed a clear trend towards language models with an ever-increasing number of parameters, as well as the growing training overhead and memory usage.
Jinda Jia, Cong Xie, Hanlin Lu, Daoce Wang, Hao Feng, Chengming Zhang, Baixi Sun, Haibin Lin, Zhi Zhang, Xin Liu, Dingwen Tao   +10 more
semanticscholar   +1 more source

MALT: distributed data-parallelism for existing ML applications

European Conference on Computer Systems, 2015
Machine learning methods, such as SVM and neural networks, often improve their accuracy by using models with more parameters trained on large numbers of examples.
Hao Li, Asim Kadav, E. Kruus, C. Ungureanu   +3 more
semanticscholar   +1 more source

Data-Parallel Sparse Factorization

SIAM Journal on Scientific Computing, 1998
The data-parallel implementation of the multifrontal algorithm for the LU factorization, without pivoting, of matrices having symmetric structure and nonsymmetric coefficients is considered. A simple yet efficient and scalable implementation of the multifrontal sparse LU factorization is presented.
Conroy, John M., Kratzer, Steven G., Lucas, Robert F., Naiman, Aaron E.   +3 more
openaire   +1 more source

Safe Data Parallelism for General Streaming

IEEE transactions on computers, 2015
Streaming applications process possibly infinite streams of data and often have both high throughput and low latency requirements. They are comprised of operator graphs that produce and consume data tuples.
S. Schneider, Martin Hirzel, B. Gedik, Kun-Lung Wu   +3 more
semanticscholar   +1 more source

Accelerating Federated Learning With Data and Model Parallelism in Edge Computing

IEEE/ACM Transactions on Networking
Recently, edge AI has been launched to mine and discover valuable knowledge at network edge. Federated Learning, as an emerging technique for edge AI, has been widely deployed to collaboratively train models on many end devices in data-parallel fashion ...
Yunming Liao, Yang Xu, Hong-Ze Xu, Zhiwei Yao, Lun Wang, C. Qiao   +5 more
semanticscholar   +1 more source

A Data-Parallel FP Compiler

Journal of Parallel and Distributed Computing, 1994
Abstract In data-parallel programming, operations are performed simultaneously on all elements of large data structures. Backus′s FP functional language promotes this view. FP provides a large set of data rearrangement primitives, and a useful set of functional combining forms that are applied to entire data structures.
Walinsky, Clifford, Banerjee, Deb
openaire   +2 more sources

Parallel functional programming on recursively defined data via data-parallel recursion

Journal of Functional Programming, 1999
This article proposes a new language mechanism for data-parallel processing of dynamically allocated recursively defined data. Different from the conventional array-based data- parallelism, it allows parallel processing of general recursively defined data such as lists or trees in a functional way.
Nishimura, Susumu, Ohori, Atsushi
openaire   +1 more source

Parallel simulation of data parallel programs

1996
Accurate simulations of parallel programs for large datasets can often be slow; parallel execution has been shown to offer significant potential in reducing the execution time of many discrete-event simulators. In this paper, we describe the design and implementation of a parallel simulator called DPSIM that simulates the execution of data parallel ...
Sundeep Prakash, Rajive Bagrodia
openaire   +1 more source