16 papers · ranked by Valyu relevance
Tingting Liu, Dong Lu, Hao Zhang, Mingyue Zheng + 6 more
'Yechun Xu' 'Cheng Luo' 'Weiliang Zhu' 'Kunqian Yu' 'Hualiang Jiang'] Title: Abstract In recent decades, high-performance computing (HPC) technologies and supercomputers in China have significantly advanced, resulting in remarkable achievements. Computational drug discovery and design, which is based on HPC and…
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…
Tiziana Castrignanò, Silvia Gioiosa, Tiziano Flati, Mirko Cestari + 9 more
'Ernesto Picardi' 'Matteo Chiara' 'Maddalena Fratelli' 'Stefano Amente' 'Marco Cirilli' 'Marco Antonio Tangaro' 'Giovanni Chillemi' 'Graziano Pesole' 'Federico Zambelli'] Background The advent of Next Generation Sequencing (NGS) technologies and the concomitant reduction in sequencing costs allows unprecedented high…
A Ravishankar Rao, Guillermo A Cecchi, Marcelo Magnasco
Background The processing of images acquired through microscopy is a challenging task due to the large size of datasets (several gigabytes) and the fast turnaround time required. If the throughput of the image processing stage is significantly increased, it can have a major impact in microscopy applications. Results We…
J. Darlington, A. J. Field, L. Hakim
We present a software framework that supports the specification of user-definable configuration options in HPC applications independently of the application code itself. Such options include model parameter values, the selection of numerical algorithm, target platform etc. and additional constraints that prevent…
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…
Julio Dondo Gazzano, Francisco Sanchez Molina, Fernando Rincon, Juan Carlos López
'Juan Carlos López'] FPGAs have shown several characteristics that make them very attractive for high performance computing (HPC). The impressive speed-up factors that they are able to achieve, the reduced power consumption, and the easiness and flexibility of the design process with fast iterations between consecutive…
Xuzhen He, Viacheslav Kovtun
The recent dramatic progress in machine learning is partially attributed to the availability of high-performant computers and development tools. The accelerated linear algebra (XLA) compiler is one such tool that automatically optimises array operations (mostly fusion to reduce memory operations) and compiles the…
Richard A. Erickson, Michael N. Fienen, S. Grace McCalla, Emily L. Weiser + 4 more
Biologists and environmental scientists now routinely solve computational problems that were unimaginable a generation ago. Examples include processing geospatial data, analyzing -omics data, and running large-scale simulations. Conventional desktop computing cannot handle these tasks when they are large, and…
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…
Miguel Ruiz-Cabello N., Maksims Abaļenkovs, Luis M. Diaz Angulo, Clemente Cobos Sanchez + 3 more
'Clemente Cobos Sanchez' 'Franco Moglie' 'Salvador G. Garcia' 'Rashid Mehmood'] This work provides an in-depth computational performance study of the parallel finite-difference time-domain (FDTD) method. The parallelization is done at various levels including: shared- (OpenMP) and distributed- (MPI) memory paradigms…
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)…
Moritz Helias, Susanne Kunkel, Gen Masumoto, Jun Igarashi + 5 more
'Jochen Martin Eppler' 'Shin Ishii' 'Tomoki Fukai' 'Abigail Morrison' 'Markus Diesmann'] NEST is a widely used tool to simulate biological spiking neural networks. Here we explain the improvements, guided by a mathematical model of memory consumption, that enable us to exploit for the first time the computational power…
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…
Francesco Cremonesi, Felix Schürmann
Computational modeling and simulation have become essential tools in the quest to better understand the brain’s makeup and to decipher the causal interrelations of its components. The breadth of biochemical and biophysical processes and structures in the brain has led to the development of a large variety of model…