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Search · four archives
25 papers · ranked by Valyu relevance
Alessandro Petrini, Marco Mesiti, Max Schubach, Marco Frasca + 7 more
The idea on which multi-core parSMURF builds is that all operations performed on the different parts of the partition can be assigned to multiple core/threads and processed in parallel. Namely, given q threads, the data parts N1, …, Nn are equally distributed among threads so that thread i receives a subset (chunk) Ci…
Alessandro Petrini, Marco Mesiti, Max Schubach, Marco Frasca + 7 more
Several prediction problems in Computational Biology and Genomic Medicine are characterized by both big data as well as a high imbalance between examples to be learned, whereby positive examples can represent a tiny minority with respect to negative examples. For instance, deleterious or pathogenic variants are…
Prerna Saini, Ankit Bansal, Abhishek Sharma
This paper presents the research work on multicore microcontrollers using parallel, and time critical programming for the embedded systems. Due to the high complexity and limitations, it is very hard to work on the application development phase on such architectures. The experimental results mentioned in the paper are…
Gabriele D’Angelo, Moreno Marzolla
Recent advances in computing architectures and networking are bringing parallel computing systems to the masses so increasing the number of potential users of these kinds of systems. In particular, two important technological evolutions are happening at the ends of the computing spectrum: at the "small" scale…
Johann M Kraus, Hans A Kestler
Background In recent years, the demand for computational power in computational biology has increased due to rapidly growing data sets from microarray and other high-throughput technologies. This demand is likely to increase. Standard algorithms for analyzing data, such as cluster algorithms, need to be parallelized…
M. Irfan Uddin
In the past, efforts were taken to improve the performance of a processor via frequency scaling. However, industry has reached the limits of increasing the frequency and therefore concurrent execution of instructions on multiple cores seems the only possible option. It is not enough to provide concurrent execution by…
Brijender Kahanwal
Nowadays, we are to find out solutions to huge computing problems very rapidly. It brings the idea of parallel computing in which several machines or processors work cooperatively for computational tasks. In the past decades, there are a lot of variations in perceiving the importance of parallelism in computing…
Ben Langmead, Christopher Wilks, Valentin Antonescu, Rone Charles
General-purpose processors can now contain many dozens of processor cores and support hundreds of simultaneous threads of execution. To make best use of these threads, genomics software must contend with new and subtle computer architecture issues. We discuss some of these and propose methods for improving thread…
Yann Garniron, Thomas Applencourt, Kevin Gasperich, Anouar Benali + 15 more
Quantum Package is an open-source programming environment for quantum chemistry specially designed for wave function methods. Its main goal is the development of determinant-driven selected configuration interaction (sCI) methods and multi-reference second-order perturbation theory (PT2). The determinant-driven…
Viacheslav Bolnykh, Jógvan Magnus Haugaard Olsen, Simone Meloni, Martin P. Bircher + 3 more
We present a highly scalable DFT-based QM/MM implementation developed within MiMiC, a recently introduced multiscale modeling framework that uses a loose-coupling strategy in conjunction with a multiple-program multiple-data (MPMD) approach. The computation of electrostatic QM/MM interactions is parallelized exploiting…
David Díaz, Francisco J. Esteban, Pilar Hernández, Juan Antonio Caballero + 4 more
'Juan Antonio Caballero' 'Antonio Guevara' 'Gabriel Dorado' 'Sergio Gálvez' 'Charles Y. Chiu'] We have developed the MC64-ClustalWP2 as a new implementation of the Clustal W algorithm, integrating a novel parallelization strategy and significantly increasing the performance when aligning long sequences in architectures…
Urmila Shrawankar, Mayuri Joshi
— In multi-core systems, various factors like inter-process communication, dependency, resource sharing and scheduling, level of parallelism, synchronization, number of available cores etc. influence the extent of possible High Performance Computing parallelization. These parameters if not managed to the root level…
K. Eric Harper, Thijmen de Gooijer
- Data race conditions in multi-tasking software applications are prevented by serializing access to shared memory resources, ensuring data consistency and deterministic behavior. Traditionally tasks acquire and release locks to synchronize operations on shared memory. Unfortunately, lock management can add significant…
Pierre Carrier, Bill Long, Richard Walsh, Jef Dawson + 4 more
High Performance Computing (HPC) Best Practice offers opportunities to implement lessons learned in areas such as computational chemistry and physics in genomics workflows, specifically Next-Generation Sequencing (NGS) workflows. In this study we will briefly describe how distributed-memory parallelism can be an…
Fen Ge, Chenchen Cui, Fang Zhou, Ning Wu + 1 more
More and more attention is being paid to the use of massive parallel computing performed on many-core Networks-on-Chip (NoC) in order to accelerate performance. Simultaneously deploying multiple applications on NoC is one feasible way to achieve this. In this paper, we propose a multi-phase-based multi-application…
Sirilak Ketchaya, Apisit Rattanatranurak
Quicksort is an important algorithm that uses the divide and conquer concept, and it can be run to solve any problem. The performance of the algorithm can be improved by implementing this algorithm in parallel. In this paper, the parallel sorting algorithm named the Multi-Deque Partition Dual-Deque Merge Sorting…
Gregor Mönke, Tim Schäfer, Mohsen Parto-Dezfouli, Diljit Singh Kajal + 3 more
We introduce an open-source Python package for the analysis of large-scale electrophysiological data called SyNCoPy, for Systems Neuroscience Computing in Python. The package includes signal processing analyses across time (e.g. time-lock analysis), frequency (e.g. power spectrum), and connectivity (e.g. coherence)…
János Végh
Computing is still based on the 70-years old paradigms introduced by von Neumann. The need for more performant, comfortable and safe computing forced to develop and utilize several tricks both in hardware and software. Till now technology enabled to increase performance without changing the basic computing paradigms.…
Sungju Lee, Heegon Kim, Yongwha Chung, Daihee Park
In transmitting image/video data over Video Sensor Networks (VSNs), energy consumption must be minimized while maintaining high image/video quality. Although image/video compression is well known for its efficiency and usefulness in VSNs, the excessive costs associated with encoding computation and complexity still…
Moises Hernandez-Fernandez, Istvan Reguly, Saad Jbabdi, Mike Giles + 2 more
The great potential of computational diffusion MRI (dMRI) relies on indirect inference of tissue microstructure and brain connections, since modelling and tractography frameworks map diffusion measurements to neuroanatomical features. This mapping however can be computationally highly expensive, particularly given the…
Authors not listed
Computing electrostatic interactions remains the bottleneck of molecular dynamics (MD) simulations despite more than a century of effort in developing methods to accelerate the calculation. Previously we have developed the Spherical Grid and Treecode (SGT) and Gauss-Legendre-Spherical-t (GLST) algorithms for…
Hao Li, Yi-Cheng Tu, Bo Zeng, Rashid Mehmood
The unrivaled computing capabilities of modern GPUs meet the demand of processing massive amounts of data seen in many application domains. While traditional HPC systems support applications as standalone entities that occupy entire GPUs, there are GPU-based DBMSs where multiple tasks are meant to be run at the same…
J. Harry Moore, Matthias R. Bauer, Jeff Guo, Atanas Patronov + 2 more
We present Icolos, a workflow manager written in Python as a tool for automating complex structure-based workflows. Icolos can be used as a standalone tool, for example in virtual screening campaigns, or can be used in conjunction with deep learning-based molecular generation facilitated for example by REINVENT, a…
Madushanka Manathunga, Hasan Metin Aktulga, Andreas W. Goetz, Kenneth M. Merz + 1 more
We have ported and optimized the GPU accelerated QUICK and AMBER based ab initio QM/MM implementation on AMD GPUs. This encompasses the entire Fock matrix build and force calculation in QUICK including one-electron integrals, two-electron repulsion integrals, exchange-correlation quadrature, and linear algebra…
Authors not listed
The era of exascale computing presents both exciting opportunities and unique challenges for quantum mechanical simulations. While the transition from petaflops to exascale computing has been marked by a steady increase in computational power, the shift towards heterogeneous architectures, particularly the dominant…