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The aim of this paper is to show that Digital Signal Processors (DSPs) can be used to efficiently implement complex algorithms. As an example we have chosen the problem of enumerating closed two-dimensional random paths. An Evaluation…

Computational Physics · Physics 2007-05-23 B. Afsari , N. Sadeghi-Meybodi , S. Rouhani

We present simulation details and results for the light hadron spectrum in N f = 2 + 1 lattice QCD with the nonperturbatively O(a)-improved Wilson quark action and the Iwasaki gauge action. Simulations are carried out at a lattice spacing…

Graphics Processing Units (GPUs) are being used in many areas of physics, since the performance versus cost is very attractive. The GPUs can be addressed by CUDA which is a NVIDIA's parallel computing architecture. It enables dramatic…

High Energy Physics - Lattice · Physics 2012-10-12 Nuno Cardoso , Marco Cardoso , Pedro Bicudo

This paper introduces Direct Simplified Symbolic Analysis (DSSA), a new method for simplifying analog circuits. Unlike traditional matrix- or graph-based techniques that are often slow and memory-intensive, DSSA treats the task as a…

Other Computer Science · Computer Science 2025-10-21 Mohammad Shokouhifar , Hossein Yazdanjouei , Gerhard-Wilhelm Weber

In this paper, we propose StruM, a novel structured mixed-precision-based deep learning inference method, co-designed with its associated hardware accelerator (DPU), to address the escalating computational and memory demands of deep…

Hardware Architecture · Computer Science 2025-05-20 Michael Wu , Arnab Raha , Deepak A. Mathaikutty , Martin Langhammer , Engin Tunali , Daksha Sharma

We propose an efficient block-encoding technique for the implementation of the Linear Combination of Hamiltonian Simulations (LCHS) for simulating dissipative initial-value problems. This algorithm approximates a target nonunitary operator…

Quantum Physics · Physics 2026-04-17 Ivan Novikau , Ilon Joseph

Classical simulation of noisy quantum circuits is essential for understanding quantum computing experiments. It enables scalable error characterization, analysis of how noise impacts quantum algorithms, and optimized implementations of…

Quantum Physics · Physics 2025-04-22 Ashe Miller , Corey Ostrove , Jordan Hines , Robin Blume-Kohout , Kevin Young , Timothy Proctor

Self-distillation (SD), a technique where a model improves itself using its own predictions, has attracted attention as a simple yet powerful approach in machine learning. Despite its widespread use, the mechanisms underlying its…

Machine Learning · Statistics 2025-11-20 Kaito Takanami , Takashi Takahashi , Ayaka Sakata

The operations used for neural network computation map favorably onto simple analog circuits, which outshine their digital counterparts in terms of compactness and efficiency. Nevertheless, such implementations have been largely supplanted…

Neural and Evolutionary Computing · Computer Science 2020-02-24 Jonathan Binas , Daniel Neil , Giacomo Indiveri , Shih-Chii Liu , Michael Pfeiffer

We report on lattice results of the form factors for semi-leptonic decays of the D_s meson to eta and eta', with n_f=2+1 configurations. The calculation contains disconnected fermion loop diagrams, which are challenging to calculate on the…

High Energy Physics - Lattice · Physics 2013-02-26 Issaku Kanamori

The polynomial subtraction method, a new numerical approach for reducing the noise variance of Lattice QCD disconnected matrix elements calculation, is introduced in this paper. We use the MinRes polynomial expansion of the QCD matrix as…

High Energy Physics - Lattice · Physics 2014-05-09 Quan Liu , Walter Wilcox , Ron Morgan

We consider a nonlocal evolution equation representing the continuum limit of a large ensemble of interacting particles on graphs forced by noise. The two principle ingredients of the continuum model are a nonlocal term and Q-Wiener process…

Numerical Analysis · Mathematics 2022-04-05 Georgi Medvedev , Gideon Simpson

Graphical Processing Units (GPUs) have recently become a valuable computing tool for the acquisition of data at high rates and for a relatively low cost. The devices work by parallelizing the code into thousands of threads, each executing a…

Instrumentation and Detectors · Physics 2016-11-16 W. Gohn

This paper investigates the application of a robust CPU-based power modelling methodology that performs an automatic search of explanatory events derived from performance counters to embedded GPUs. A 64-bit Tegra TX1 SoC is configured with…

Other Computer Science · Computer Science 2020-06-23 Jose Nunez-Yanez , Kris Nikov , Kerstin Eder , Mohammad Hosseinabady

In this work we explore the performance of CUDA in quenched lattice SU(2) simulations. CUDA, NVIDIA Compute Unified Device Architecture, is a hardware and software architecture developed by NVIDIA for computing on the GPU. We present an…

High Energy Physics - Lattice · Physics 2015-03-17 Nuno Cardoso , Pedro Bicudo

Due to improvements in computer performance and algorithms, the rapidly increasing cost for unquenched Wilson-type fermions with lighter quarks has been ameliorated and new simulations are now possible. Here we present results using two…

High Energy Physics - Lattice · Physics 2008-11-26 M. Göckeler , R. Horsley , Y. Nakamura , D. Pleiter , P. E. L. Rakow , G. Schierholz , W. Schroers , T. Streuer , H. Stüben , J. M. Zanotti

A graphene-based spin-diffusive (GrSD) neural network is presented in this work that takes advantage of the locally tunable spin transport of graphene and the non-volatility of nanomagnets. By using electrostatically gated graphene as…

Applied Physics · Physics 2017-12-05 Jiaxi Hu , Gordon Stecklein , Yoska Anugrah , Paul A. Crowell , Steven J. Koester

Two-loop contributions to the muon (g-2) from fermion/sfermion loops in the MSSM are presented, and an overview of the full MSSM prediction for (g-2) is given with emphasis on the behaviour in scenarios which are compatible with LHC data,…

High Energy Physics - Phenomenology · Physics 2015-06-17 Helvecio Fargnoli , Christoph Gnendiger , Sebastian Passehr , Dominik Stöckinger , Hyejung Stöckinger-Kim

Noise detrimentally affects quantum computations so that they not only become less accurate but also easier to simulate classically as systems scale up. We construct a classical simulation algorithm, LOWESA (low weight efficient simulation…

Quantum Physics · Physics 2023-06-09 Enrico Fontana , Manuel S. Rudolph , Ross Duncan , Ivan Rungger , Cristina Cîrstoiu

Precision phenomenological studies of high-multiplicity scattering processes at collider experiments present a substantial theoretical challenge and are vitally important ingredients in experimental measurements. Machine learning technology…

High Energy Physics - Phenomenology · Physics 2023-02-20 Ryan Moodie
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