24 papers · ranked by Valyu relevance
Konstantinos Rallis, Ioannis Liliopoulos, Georgios D. Varsamis, Evangelos Tsipas + 3 more
The connection and eventual integration of High-Performance Computing (HPC) with Quantum Computing (QC) represents a transformative advancement in computational technology, promising significant enhancements in solving complex, previously intractable problems. This manuscript provides a comprehensive overview of the…
Claude Tadonki
High Performance Computing (HPC) aims at providing reasonably fast computing solutions to scientific and real life problems. Many efforts have been made on the way to powerful supercomputers, including generic and customized configurations. The advent of multicore architectures is noticeable in the HPC history, because…
Daniel A. Reed, Dennis Gannon, Jack Dongarra
The world of computing is in rapid transition, now dominated by a world of smartphones and cloud services, with profound implications for the future of advanced scientific computing. Simply put, highperformance computing (HPC) is at an important inflection point. For the last 60 years, the world's fastest…
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…
John Kruper, Ariel Rokem
Tractography based on diffusion-weighted MRI (dMRI) is the predominant in vivo method for mapping the brain’s white matter. However, it is also one of the most computationally demanding steps in neuroimaging data analysis-requiring the generation and filtering of millions of streamlines per subject. Over the past…
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…
Giuliano Taffoni, G. Murante, L. Tornatore, David Goz + 4 more
'Manolis Katevenis' 'Nikolaos Chrysos' 'Manolis Marazakis'] High performance computing numerical simulations are today one of the more effective instruments to implement and study new theoretical models, and they are mandatory during the preparatory phase and operational phase of any scientific experiment. New…
Ivan Merelli, Horacio Pérez-Sánchez, Sandra Gesing, Daniele D'Agostino
"Daniele D'Agostino"] Omics sciences are able to produce, with the modern high-throughput techniques of analytical chemistry and molecular biology, a huge amount of data. Next generation sequencing (NGS) analysis of diseased somatic cells, genome wide identification of regulatory elements and biomarkers, systems…
Wei Wang, Lifan Xu, John Cavazos, Howie H. Huang + 2 more
'Tobias Preis'] Recent developments in modern computational accelerators like Graphics Processing Units (GPUs) and coprocessors provide great opportunities for making scientific applications run faster than ever before. However, efficient parallelization of scientific code using new programming tools like CUDA requires…
János Végh
—More than hundred years ago the classic physics was in its full power, with just a few unexplained phenomena; which, however, led to a revolution and the development of the modern physics. The outbreak was possible by studying the nature under extreme conditions which finally led to the understanding of the…
Torsten Hoefler, Marcin Copik, Pete Beckman, Andrew Jones + 7 more
'Ian Foster' 'Manish Parashar' 'Daniel A. Reed' 'Matthias Troyer' 'T. C. Schulthess' 'Daniel Ernst' 'Jack Dongarra'] HPC and Cloud have evolved independently, specializing their innovations into performance or productivity. Acceleration as a Service (XaaS) is a recipe to empower both fields with a shared execution…
János Végh
With both knowing more and more details about how neurons and complex neural networks work and having serious demand for making performable huge artificial networks, more and more efforts are devoted to build both hardware and/or software simulators and supercomputers targeting artificial intelligence applications…
Joseph Moon, Peer-Timo Bremer, Pratik Mukherjee, Amy J. Markowitz + 5 more
Large scale diffusion MRI tractography remains a significant challenge. Users must orchestrate a complex sequence of instructions that require many software packages with complex dependencies and high computational cost. We developed MaPPeRTrac, a diffusion MRI tractography pipeline that simplifies and vastly…
Rene Miedema, Christos Strydis
Introduction In-silico simulations are a powerful tool in modern neuroscience for enhancing our understanding of complex brain systems at various physiological levels. To model biologically realistic and detailed systems, an ideal simulation platform must possess: (1) high performance and performance scalability, (2)…
Marissa E. Powers, Keith Mannthey, Priyanka Sebastian, Snehal Adsule + 6 more
Next Generation Sequencing (NGS) workloads largely consist of pipelines of tasks with heterogeneous compute, memory, and storage requirements. Identifying the optimal system configuration has historically required expertise in both system architecture and bioinformatics. This paper outlines infrastructure…
Jamie Alnasir, Hugh P. Shanahan
The paper reviews the use of the Hadoop platform in Structural Bioinformatics applications. Specifically, we review a number of implementations using Hadoop of high-throughput analyses, e.g. ligand-protein docking and structural alignment, and their scalability in comparison with other batch schedulers and MPI. We find…
Hammad Ather, Sophie Berkman, Giuseppe Cerati, Matti J. Kortelainen + 9 more
Traditionally, high energy physics (HEP) experiments have relied on x86 CPUs for the majority of their significant computing needs. As the field looks ahead to the next generation of experiments such as DUNE and the High-Luminosity LHC, the computing demands are expected to increase dramatically. To cope with this…
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…
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
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…
Authors not listed
Imagine a computer capable of solving currently unsolvable problems. Quantum computing leverages the principles of quantum mechanics to tackle complex challenges that would take classical computers centuries to complete. In this Commentary, we explore the current state of quantum computing development and how it will…
Maxim Lippeveld, Daniel Peralta, Andrew Filby, Yvan Saeys
Due to high resolution and throughput of modern image cytometry platforms, morphologically profiling generated datasets poses a significant computational challenge. Here, we present Scalable Cytometry Image Processing (SCIP), an image processing software aimed at running on distributed high performance computing…
Yingqi Tian, Zhaoxuan Xie, Zhen Luo, Haibo Ma
Using the mixed precision strategy to optimize quantum chemistry codes has been proved promising in saving computational cost and maintaining chemical accuracy. Here, an efficient mixed-precision density matrix renormalization group (DMRG) scheme, containing a two-level mixed-precision hierarchy, is developed and…
Authors not listed
We describe a collaborative research project spanning the disciplines of quantum hardware, quantum algorithms, conventional computational chemistry, synthetic medicinal chemistry and life sciences. Our project seeks to demonstrate an impact of quantum computing on human health. It is one of several funded by Wellcome…