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In-memory computing is an emerging computing paradigm that overcomes the limitations of exiting Von-Neumann computing architectures such as the memory-wall bottleneck. In such paradigm, the computations are performed directly on the data…

Emerging Technologies · Computer Science 2022-04-14 Mohammed E. Fouda , Hasan Erdem Yantir , Ahmed M. Eltawil , Fadi Kurdahi

The trend towards highly parallel multi-processing is ubiquitous in all modern computer architectures, ranging from handheld devices to large-scale HPC systems; yet many applications are struggling to fully utilise the multiple levels of…

Distributed, Parallel, and Cluster Computing · Computer Science 2013-07-19 Michael Lange , Gerard Gorman , Michele Weiland , Lawrence Mitchell , Xiaohu Guo , James Southern

Optimistic parallelization is a promising approach for the parallelization of irregular algorithms: potentially interfering tasks are launched dynamically, and the runtime system detects conflicts between concurrent activities, aborting and…

Programming Languages · Computer Science 2012-06-28 Francesco Versaci , Keshav Pingali

Minimum Spanning Tree (MST) is an important graph algorithm that has wide ranging applications in the areas of computer networks, VLSI routing, wireless communications among others. Today virtually every computer is built out of multi-core…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-05-15 Suryanarayana Murthy Durbhakula

For over a decade now we have been witnessing the success of {\em massive parallel computation} (MPC) frameworks, such as MapReduce, Hadoop, Dryad, or Spark. One of the reasons for their success is the fact that these frameworks are able to…

Data Structures and Algorithms · Computer Science 2018-02-02 Artur Czumaj , Jakub Łącki , Aleksander Mądry , Slobodan Mitrović , Krzysztof Onak , Piotr Sankowski

The growing complexity of real-world systems necessitates interdisciplinary solutions to confront myriad challenges in modeling, analysis, management, and control. To meet these demands, the parallel systems method rooted in Artificial…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-03-26 Yong Zhao , Zhengqiu Zhu , Bin Chen , Sihang Qiu , Jincai Huang , Xin Lu , Weiyi Yang , Chuan Ai , Kuihua Huang , Cheng He , Yucheng Jin , Zhong Liu , Fei-Yue Wang

Modern learning models are characterized by large hyperparameter spaces and long training times. These properties, coupled with the rise of parallel computing and the growing demand to productionize machine learning workloads, motivate the…

Machine Learning · Computer Science 2020-03-17 Liam Li , Kevin Jamieson , Afshin Rostamizadeh , Ekaterina Gonina , Moritz Hardt , Benjamin Recht , Ameet Talwalkar

The growth in the use of computationally intensive statistical procedures, especially with Big Data, has necessitated the usage of parallel computation on diverse platforms such as multicore, GPU, clusters and clouds. However, slowdown due…

Computation · Statistics 2014-09-23 Norman Matloff

We discuss how string sorting algorithms can be parallelized on modern multi-core shared memory machines. As a synthesis of the best sequential string sorting algorithms and successful parallel sorting algorithms for atomic objects, we…

Data Structures and Algorithms · Computer Science 2014-03-11 Timo Bingmann , Andreas Eberle , Peter Sanders

Our ISCA 2015 paper provides a new programmable processing-in-memory (PIM) architecture and system design that can accelerate key data-intensive applications, with a focus on graph processing workloads. Our major idea was to completely…

Hardware Architecture · Computer Science 2023-06-28 Junwhan Ahn , Sungpack Hong , Sungjoo Yoo , Onur Mutlu , Kiyoung Choi

RSA is one of the most popular Public Key Cryptography based algorithm mainly used for digital signatures, encryption/decryption etc. It is based on the mathematical scheme of factorization of very large integers which is a…

Cryptography and Security · Computer Science 2015-03-13 Sapna Saxena , Bhanu Kapoor

Graph clustering has many important applications in computing, but due to growing sizes of graphs, even traditionally fast clustering methods such as spectral partitioning can be computationally expensive for real-world graphs of interest.…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-06-11 Julian Shun , Farbod Roosta-Khorasani , Kimon Fountoulakis , Michael W. Mahoney

The advent of high performance computing (HPC) and graphics processing units (GPU), present an enormous computation resource for Large data transactions (big data) that require parallel processing for robust and prompt data analysis. While…

Distributed, Parallel, and Cluster Computing · Computer Science 2014-10-17 Kato Mivule , Benjamin Harvey , Crystal Cobb , Hoda El Sayed

Identifying the connected components of a graph, apart from being a fundamental problem with countless applications, is a key primitive for many other algorithms. In this paper, we consider this problem in parallel settings. Particularly,…

Data Structures and Algorithms · Computer Science 2020-03-13 Soheil Behnezhad , Laxman Dhulipala , Hossein Esfandiari , Jakub Łącki , Vahab Mirrokni

Answer Set Programming (ASP) is a powerful logic-based programming language, which is enjoying increasing interest within the scientific community and (very recently) in industry. The evaluation of ASP programs is traditionally carried out…

Programming Languages · Computer Science 2011-10-14 Simona Perri , Francesco Ricca , Marco Sirianni

We consider learning problems over training sets in which both, the number of training examples and the dimension of the feature vectors, are large. To solve these problems we propose the random parallel stochastic algorithm (RAPSA). We…

Machine Learning · Computer Science 2016-06-17 Aryan Mokhtari , Alec Koppel , Alejandro Ribeiro

We investigate distributed memory parallel sorting algorithms that scale to the largest available machines and are robust with respect to input size and distribution of the input elements. The main outcome is that four sorting algorithms…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-01-17 Michael Axtmann , Peter Sanders

Since the very beginning of hardware development, computer processors were invented with ever-increasing clock frequencies and sophisticated in-build optimization strategies. Due to physical limitations, this 'free lunch' of speedup has…

Distributed, Parallel, and Cluster Computing · Computer Science 2008-10-31 Peter Tröger

Answer Set Programming (ASP) has become, the paradigm of choice in the field of logic programming and non-monotonic reasoning. Thanks to the availability of efficient solvers, ASP has been successfully employed in a large number of…

Artificial Intelligence · Computer Science 2019-09-05 Agostino Dovier , Andrea Formisano , Flavio Vella

Machine learning potentials have achieved great success in accelerating atomistic simulations. Many of them relying on atom-centered local descriptors are natural for parallelization. More recent message passing neural network (MPNN) models…

Chemical Physics · Physics 2025-06-10 Junfan Xia , Bin Jiang