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This letter compares the performance of four different, popular simulation environments for robotics and reinforcement learning (RL) through a series of benchmarks. The benchmarked scenarios are designed carefully with current industrial…

Robotics · Computer Science 2021-03-09 Marian Körber , Johann Lange , Stephan Rediske , Simon Steinmann , Roland Glück

Generalized-ensemble Monte Carlo simulations such as the multicanonical method and similar techniques are among the most efficient approaches for simulations of systems undergoing discontinuous phase transitions or with rugged free- energy…

Computational Physics · Physics 2018-02-06 Jonathan Gross , Johannes Zierenberg , Martin Weigel , Wolfhard Janke

Nowadays, several industrial applications are being ported to parallel architectures. These applications take advantage of the potential parallelism provided by multiple core processors. Many-core processors, especially the GPUs(Graphics…

Distributed, Parallel, and Cluster Computing · Computer Science 2011-03-28 Wendell Rodrigues , Frédéric Guyomarc'h , Jean-Luc Dekeyser

Multithreaded Multi-core processors are prevalent today and are used for solving some of the important problems in computing. Resource imbalance can negatively impact overall performance in such processors. Hence balanced resource…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-08-25 Suryanarayana Murthy Durbhakula

We discuss the advantages of parallelization by multithreading on graphics processing units (GPUs) for parallel tempering Monte Carlo computer simulations of an exemplified bead-spring model for homopolymers. Since the sampling of a large…

Computational Physics · Physics 2015-05-28 Jonathan Groß , Wolfhard Janke , Michael Bachmann

We present a case-study on the utility of graphics cards to perform massively parallel simulation of advanced Monte Carlo methods. Graphics cards, containing multiple Graphics Processing Units (GPUs), are self-contained parallel…

Computation · Statistics 2015-05-05 Anthony Lee , Christopher Yau , Michael B. Giles , Arnaud Doucet , Christopher C. Holmes

Micro-macro models provide a powerful tool to study the relationship between microscale mechanisms and emergent macroscopic behavior. However, the detailed microscopic modeling may require tracking and evolving a high-dimensional…

Computational Physics · Physics 2019-08-13 Steven Cook , Tamar Shinar

Processors with large numbers of cores are becoming commonplace. In order to take advantage of the available resources in these systems, the programming paradigm has to move towards increased parallelism. However, increasing the level of…

Distributed, Parallel, and Cluster Computing · Computer Science 2014-10-07 Ashkan Tousimojarad , Wim Vanderbauwhede

Parallel algorithms relying on synchronous parallelization libraries often experience adverse performance due to global synchronization barriers. Asynchronous many-task runtimes offer task futurization capabilities that minimize or remove…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-06-05 Alexander Strack , Christopher Taylor , Patrick Diehl , Dirk Pflüger

The parallelism afforded by GPUs presents significant advantages in training controllers through reinforcement learning (RL). However, integrating model-based optimization into this process remains challenging due to the complexity of…

Robotics · Computer Science 2024-08-20 Se Hwan Jeon , Seungwoo Hong , Ho Jae Lee , Charles Khazoom , Sangbae Kim

The shrinking of transistor geometries as well as the increasing complexity of integrated circuits, significantly aggravate nonlinear design behavior. This demands accurate and fast circuit simulation to meet the design quality and…

Signal Processing · Electrical Eng. & Systems 2020-02-14 Mohammad Saeed Abrishami , Hao Ge , Justin F. Calderon , Massoud Pedram , Shahin Nazarian

LLM training is scaled up to 10Ks of GPUs by a mix of data-(DP) and model-parallel (MP) execution. Critical to achieving efficiency is tensor-parallel (TP; a form of MP) execution within tightly-coupled subsets of GPUs, referred to as a…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-04-09 Daiyaan Arfeen , Dheevatsa Mudigere , Ankit More , Bhargava Gopireddy , Ahmet Inci , Gregory R. Ganger

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

Nowadays, several industrial applications are being ported to parallel architectures. In fact, these platforms allow acquire more performance for system modelling and simulation. In the electric machines area, there are many problems which…

Distributed, Parallel, and Cluster Computing · Computer Science 2010-10-25 Antonio Wendell De Oliveira Rodrigues , Frédéric Guyomarch , Yvonnick Le Menach , Jean-Luc Dekeyser

Many-core accelerators, as represented by the XeonPhi coprocessors and GPGPUs, allow software to exploit spatial and temporal sharing of computing resources to improve the overall system performance. To unlock this performance potential…

Performance · Computer Science 2018-02-09 Peng Zhang , Jianbin Fang , Tao Tang , Canqun Yang , Zheng Wang

Motion planning is a fundamental problem in robotics that involves generating feasible trajectories for a robot to follow. Recent advances in parallel computing, particularly through CPU and GPU architectures, have significantly reduced…

Robotics · Computer Science 2025-05-13 Jiaming Hu , Jiawei Wang , Henrik Christensen

The Kernel Polynomial Method (KPM) is one of the fast diagonalization methods used for simulations of quantum systems in research fields of condensed matter physics and chemistry. The algorithm has a difficulty to be parallelized on a…

Computational Physics · Physics 2011-05-30 Shixun Zhang , Shinichi Yamagiwa , Masahiko Okumura , Seiji Yunoki

The advent of hardware ray tracing (RT) units has brought unprecedented realism to real-time rendered computer graphics. However, the potential of these units extends beyond graphics, offering acceleration for various computational tasks…

Hardware Architecture · Computer Science 2025-05-22 Fangjia Shen , Aaron Barnes , Anusuya Nallathambi , Timothy G. Rogers

Ring-Learning-with-Errors (RLWE) has emerged as the foundation of many important techniques for improving security and privacy, including homomorphic encryption and post-quantum cryptography. While promising, these techniques have received…

Programmable Logic Devices (PLDs) continue to grow in size and currently contain several millions of gates. At the same time, research effort is going into higher-level hardware synthesis methodologies for reconfigurable computing that can…

Programming Languages · Computer Science 2019-05-24 Issam Damaj