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The increasing number of processing elements and decreas- ing memory to core ratio in modern high-performance platforms makes efficient strong scaling a key requirement for numerical algorithms. In order to achieve efficient scalability on…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-01-14 Michael Lange , Gerard Gorman , Michele Weiland , Lawrence Mitchell , James Southern

Control parallelism and data parallelism is mostly reasoned and optimized as separate functions. Because of this, workloads that are irregular, fine-grain and dynamic such as dynamic graph processing become very hard to scale. An…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-03-08 Bibrak Qamar Chandio , Thomas Sterling , Prateek Srivastava

We evaluate optimized parallel sparse matrix-vector operations for two representative application areas on widespread multicore-based cluster configurations. First the single-socket baseline performance is analyzed and modeled with respect…

Performance · Computer Science 2012-03-01 Gerald Schubert , Georg Hager , Holger Fehske , Gerhard Wellein

A new high-level interface to multi-threading in Prolog, implemented in hProlog, is described. Modern CPUs often contain multiple cores and through high-level multi-threading a programmer can leverage this power without having to worry…

Programming Languages · Computer Science 2011-12-26 Timon Van Overveldt , Bart Demoen

Structured matrices with symbolic sizes appear frequently in the literature, especially in the description of algorithms for linear algebra. Recent work has treated these symbolic structured matrices themselves as computational objects,…

Symbolic Computation · Computer Science 2023-11-29 Mike Ghesquiere , Stephen M. Watt

Algorithmic skeletons are used as building-blocks to ease the task of parallel programming by abstracting the details of parallel implementation from the developer. Most existing libraries provide implementations of skeletons that are…

Programming Languages · Computer Science 2016-07-11 Venkatesh Kannan , G. W. Hamilton

Multi-objective integer optimization problems are hard to solve, mainly because the number of nondominated images is often extremely large. We present the first exact algorithm, called PEA, that fully utilizes the multicore architecture of…

Optimization and Control · Mathematics 2026-02-13 Kathrin Prinz , Levin Nemesch , Stefan Ruzika

We implemented a parallel version of the multicanonical algorithm and applied it to a variety of systems with phase transitions of first and second order. The parallelization relies on independent equilibrium simulations that only…

Computational Physics · Physics 2015-01-27 Johannes Zierenberg , Martin Marenz , Wolfhard Janke

The tremendous advance in computer technology in the past decade has made it possible to achieve the performance of a supercomputer on a very small budget. We have built a multi-CPU cluster of Pentium PC capable of parallel computations…

Distributed, Parallel, and Cluster Computing · Computer Science 2009-11-07 X. Q. Luo , E. B. Gregory , J. C. Yang , Y. L. Wang , D. Chang , Y. Lin

Simulations of systems with quenched disorder are extremely demanding, suffering from the combined effect of slow relaxation and the need of performing the disorder average. As a consequence, new algorithms, improved implementations, and…

Computational Physics · Physics 2020-05-20 Ravinder Kumar , Jonathan Gross , Wolfhard Janke , Martin Weigel

The quantum machine learning model is emerging as a new model that merges quantum computing and machine learning. Simulating very deep quantum machine learning models requires a lot of resources, increasing exponentially based on the number…

Quantum Physics · Physics 2025-02-18 Vu Tuan Hai , Le Vu Trung Duong , Pham Hoai Luan , Yasuhiko Nakashima

In this paper, we evaluate the performance of various parallel optimization methods for Kernel Support Vector Machines on multicore CPUs and GPUs. In particular, we provide the first comparison of algorithms with explicit and implicit…

Machine Learning · Computer Science 2014-04-04 Stephen Tyree , Jacob R. Gardner , Kilian Q. Weinberger , Kunal Agrawal , John Tran

We describe a system that simplifies the process of debugging programs produced by computer-aided parallelization tools. The system uses relative debugging techniques to compare serial and parallel executions in order to show where the…

Software Engineering · Computer Science 2007-05-23 Robert Hood , Gabriele Jost

Recent work showed that compiling functional programs to use dense, serialized memory representations for recursive algebraic datatypes can yield significant constant-factor speedups for sequential programs. But serializing data in a…

Programming Languages · Computer Science 2021-07-02 Chaitanya Koparkar , Mike Rainey , Michael Vollmer , Milind Kulkarni , Ryan R. Newton

Parallel processing is considered as todays and future trend for improving performance of computers. Computing devices ranging from small embedded systems to big clusters of computers rely on parallelizing applications to reduce execution…

Distributed, Parallel, and Cluster Computing · Computer Science 2014-11-27 Oussama Tahan

Since the days of OpenMP 1.0 computer hardware has become more complex, typically by specializing compute units for coarse- and fine-grained parallelism in incrementally deeper hierarchies of parallelism. Newer versions of OpenMP reacted by…

Programming Languages · Computer Science 2023-09-06 Michael Kruse

We build on a fine-grained analysis of session-based interaction as provided by the linear logic typing disciplines to introduce the SAM, an abstract machine for mechanically executing session-typed processes. A remarkable feature of the…

Programming Languages · Computer Science 2024-01-22 Luís Caires , Bernardo Toninho

We show that a constant number of self-attention layers can efficiently simulate, and be simulated by, a constant number of communication rounds of Massively Parallel Computation. As a consequence, we show that logarithmic depth is…

Machine Learning · Computer Science 2024-02-15 Clayton Sanford , Daniel Hsu , Matus Telgarsky

We describe a family of MPI applications we call the Parallel Unix Commands. These commands are natural parallel versions of common Unix user commands such as ls, ps, and find, together with a few similar commands particular to the parallel…

Distributed, Parallel, and Cluster Computing · Computer Science 2007-05-23 E. Ong , E. Lusk , W. Gropp

The prefix sum operation is a useful primitive with a broad range of applications. For database systems, it is a building block of many important operators including join, sort and filter queries. In this paper, we study different methods…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-12-25 Wangda Zhang , Yanbin Wang , Kenneth A. Ross
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