Davor Davidovic

Ruđer Bošković Institute | RBI · Centre for Informatics and Computing

Background Traditional publishing models, open access and major publishers, cannot adequately address the key challenges of academic publishing today: Speed of peer review, recognition of work and incentive mechanisms, transparency and thrust of the system. Methods To address these challenges, the authors propose Democratisation of Academic Publish...

This study investigates the usability and applicability of High-Performance Computing (HPC) in photogrammetry for the creation of high-resolution 3D models for the preservation of cultural heritage. The study addresses the challenges posed by the large datasets generated for high-resolution photogrammetry and argues in favour of the potential of HP...

It is widely accepted that the dynamic of entanglement in presence of a generic circuit can be predicted by the knowledge of the statistical properties of the entanglement spectrum. We tested this assumption by applying a Metropolis-like entanglement cooling algorithm generated by different sets of local gates, on states sharing the same statistic....

Dew computing, a new version of the computing paradigm appeared along with cloud, edge, and fog computing. Dew computing is a distributed computing framework that is deliberated as an augmentation in the cloud computing schema. Researchers and academic practitioners have explored the concept of dew computing since its germination. In dew computing,...

Background: Traditional publishing models, open access and major publishers, cannot adequately address the key challenges of academic publishing today: Speed of peer review, recognition of work and incentive mechanisms, transparency and thrust of the system. Methods: To address these challenges, the authors propose Decentralised Academic Publishing...

It is widely accepted that the dynamic of entanglement in presence of a generic circuit can be predicted by the knowledge of the statistical properties of the entanglement spectrum. We tested this assumption by applying a Metropolis-like entanglement cooling algorithm generated by different sets of local gates, on states sharing the same statistic....

Coastal water quality management is a public health concern, as water of poor quality can potentially harbor dangerous pathogens. In this study, we employ routine monitoring data of EscherichiaColi and enterococci across 15 beaches in the city of Rijeka, Croatia, to build machine learning models for predicting E.Coli and enterococci based on enviro...

As modern massively parallel clusters are getting larger with beefier compute nodes, traditional parallel eigensolvers, such as direct solvers, struggle keeping the pace with the hardware evolution and being able to scale efficiently due to additional layers of communication and synchronization. This difficulty is especially important when porting...

One of the most important and commonly used operations in many linear algebra functions is matrix-matrix multiplication (GEMM), which is also a key component in obtaining high performance of many scientific codes. It is a computationally intensive function requiring $O(n^3)$ operations, and its high computational intensity makes it well-suited to b...

Coastal water quality management is a public health concern, as poor coastal water quality can harbor pathogens that are dangerous to human health. Tourism-oriented countries need to actively monitor the condition of coastal water at tourist popular sites during the summer season. In this study, routine monitoring data of $Escherichia\ Coli$ and en...

Spike glycoprotein is essential for the reproduction of the SARS-CoV-2 virus, and its inhibition using already approved antiviral drugs may open new avenues for treatment of patients with the COVID-19 disease. Because of that we analyzed the inhibition of SARS-CoV-2 spike glycoprotein with FDA-approved antiviral drugs and their double and triple co...

The calculation of overlaps between many-electron wave functions at different nuclear geometries during nonadiabatic dynamics simulations requires the evaluation of a large number of determinants of matrices that differ only in a few rows/columns. While this calculation is fast for small systems, its cost grows faster than the alternative electroni...

In this study, we investigated the inhibition of SARS-CoV-2 spike glycoprotein with HIV drugs and their combinations. This glycoprotein is essential for the reproduction of the SARS-COV-2 virus, so its inhibition opens new avenues for the treatment of patients with COVID-19 disease. In doing so, we used the VINI in silico model of cancer, whose hig...

We introduce a new algorithm that exploits the relationship between the determinants of a sequence of matrices that appear in the calculation of many-electron wave function overlaps, yielding a considerable reduction of the theoretical cost. The resulting enhanced algorithm is embarrassingly parallel and our comparison against the (embarrassingly p...

Two algorithms for calculating overlaps between CIS (or TDDFT) type excited state wave functions are presented, one based on an expansion of overlap determinants into level 2 minors (OL2M) and the other based on an expansion of the wave functions into natural transition orbitals (ONTO). Both algorithms are significantly faster than previously avail...

The rapid development of new digital tools and infrastructures in recent years and their application to a variety of disciplines has transformed how we store, access and retrieve information available to us. This has also shaped the ways how knowledge in a diverse cultural context is presented, used and re-used. The exploreAT! project builds upon n...

In the framework of the H2020 INDIGO-DataCloud project, we have implemented an advanced solution for the automatic deployment of digital data repositories based on Invenio, the digital library framework developed by CERN. Exploiting cutting-edge technologies, such as Docker and Apache Mesos, and standard specifications to describe application archi...

This paper describes the achievements of the H2020 project INDIGO-DataCloud. The project has provided e-infrastructures with tools, applications and cloud framework enhancements to manage the demanding requirements of scientific communities, either locally or through enhanced interfaces. The middleware developed allows to federate hybrid resources,...

In the framework of the H2020 INDIGO-DataCloud project we have implemented an advanced solution for the automatic deployment of digital data repositories based on Invenio, the digital library framework developed by Cern. Exploiting cutting-edge technologies, like docker and Apache Mesos, and standard interfaces like TOSCA we are able to provide a s...

Legacy codes in computational science and engineering have been very successful in providing essential functionality to researchers. However, they are not capable of exploiting the massive parallelism provided by emerging heterogeneous architectures. The lack of portable performance and scalability puts them at high risk: either they evolve or they...

Presentation at Methods in dialectology XVI, Tokyo, Japan. http://pj.ninjal.ac.jp/Methodsxvi/abs/Wandl-Vogt-2.pdf

In this paper we focus on the integration of high-performance numerical libraries in ab initio codes and the portability of performance and scalability. The target of our work is FLEUR, a software for electronic structure calculations developed in the Forschungszentrum Jülich over the course of two decades. The presented work follows up on a previo...

In this paper we focus on the integration of high-performance numerical libraries in ab initio codes and the portability of performance and scalability. The target of our work is FLEUR, a software for electronic structure calculations developed in the Forschungszentrum J\"ulich over the course of two decades. The presented work follows up on a prev...

For many years Apache Hadoop has been used as a synonym for processing data in the MapReduce fashion. However, due to the complexity of developing MapReduce applications, adoption of this paradigm in genetics has been limited. To alleviate some of the issues, we have previously developed Cloudflow - a high-level pipeline framework that allows users...

The increasing energy consumption of large-scale high performance resources raises technical and economical concerns. A reduction of consumed energy in multicore systems is possible to some extent with an optimized usage of computing and memory resources that is tailored to specific HPC applications. The essential step towards more sustainable cons...

The paper considers the conceptual approach for organization of the vertical hierarchical links between the scalable distributed computing paradigms: Cloud Computing, Fog Computing and Dew Computing. In this paper, the Dew Computing is described and recognized as a new structural layer in the existing distributed computing hierarchy. In the existin...

The paper considers the conceptual approach for organization of the vertical hierarchical links between the scalable distributed computing paradigms: Cloud Computing, Fog Computing and Dew Computing. In this paper, the Dew Computing is described and recognized as a new structural layer in the existing distributed computing hierarchy. In the existin...

We leverage CUDA dynamic parallelism to reduce execution time while significantly reducing energy consumption of the Conjugate Gradient (CG) method for the iterative solution of sparse linear systems on graphics processing units (GPUs). Our new implementation of this solver is launched from the CPU in the form of a single “parent” CUDA kernel, whic...

The data-driven parallelization framework Hadoop MapReduce allows analysing large data sets in a scalable way. Since the development of MapReduce programs can be a time-intensive and challenging task, the application and usage of Hadoop in Biomedical Research is still limited. Here we present Cloudflow, a high-level framework to hide the implementa...

We address the solution of large-scale eigenvalue problems that appear in the motion simulation of complex macromolecules on multithreaded platforms, consisting of multicore processors and possibly a graphics processor (graphics processing unit). In particular, we compare specialized implementations of several high-performance eigensolvers that, by...

We consider the solution of large-scale eigenvalue problems that appear in the motion simulation of complex macromolecules on desktop platforms. To tackle the dimension of the matrices that are involved in these problems, we formulate out-of-core (OOC) variants of the two selected eigensolvers, that basically decouple the performance of the solver...

The ever-increasing data production and availability in the field of bioinformatics demands a paradigm shift towards the utilization of novel solutions for efficient data storage and processing, such as the MapReduce data parallel programming model and the corresponding Apache Hadoop framework. Despite the evident potential of this model and existe...

Today we witness the exponential growth of scientific research. This fast growth is possible thanks to the rapid development of computing systems since its first days in 1947 and the invention of transistor till the present days with high performance and scalable distributed computing systems. This fast growth of computing systems was first observe...

The Travelling Salesman Problem (TSP) is one of the most studied combinatorial optimization problem which is significant in many practical applications in transportation field. The TSP is an NP-hard problem and requires large computational power to be optimally solved by exact algorithms. In the past few years, fast development of general-purpose G...

Marine traffic and rapidly growing tourism in the Adriatic Sea region are the main reasons for investigating different weather phenomena and developing the prediction models that depend on distributed computing infrastructures. Weather phenomena like storms and waterspouts are common in the in the Mediterranean Basin and thus in the Adriatic Sea re...

In this paper we address the reduction of a dense matrix to tridiagonal form for the solution of symmetric eigen value problems on a graphics processor (GPU) when the data is too large to fit into the accelerator memory. We apply out of-core techniques to a three-stage algorithm, carefully redesigning the first stage to reduce the number of data tr...

Cloud computing has revolutionized how availability and access to computing and storage resources is realized; it has made it possible to provision a large computational infrastructure in a matter of minutes, all through a web browser. What it has not yet solved is accessibility of a tool execution environment where tools and data can easily be add...

We compare two approaches to compute a portion of the spectrum of dense symmetric definite generalized eigenproblems: one is based on the reduction to tridiagonal form, and the other on the Krylov-subspace iteration. Two large-scale applications, arising in molecular dynamics and material science, are employed to investigate the contributions of th...

The paper describes several efficient parallel implementations of the one-sided hyperbolic Jacobi-type algorithm for computing eigenvalues and eigenvectors of Hermitian matrices. By appropriate blocking of the algorithms an almost ideal load balancing between all available processors/cores is obtained. A similar blocking technique can be used to ex...

The numerical weather prediction models demand large execution time and resource allocation; therefore we need large parallel computation facilities, like the grid systems, in order to execute them. In this paper the implementation of the Advanced Weather Research and Forecasting (WRF-ARW) model on the SEEGRID-SCI grid infrastructure is presented....

In this work the application of the Advanced Weather Research and Forecasting (WRF-ARW) model on the Grid infrastructure will be presented. Using WRF-ARW model and Grid infrastructure is very important to achieve a good weather forecast for small and large regions, but also it's better to understand how weather behaves in very complex situation or...

Atmospheric science is advancing towards very complex phenomena at ever smaller temporal and spatial scales. One of the principal tools utilized in atmospheric science are weather prediction models. These models usually demand large execution times and resource allocation, such as CPU time and storage space. The main goal of our research is porting...

Recent advances in fast implementation of the indefinite one‐sided Jacobi method are described. Special attention is devoted to the block pivot strategies and to the column sorting which is embedded in the algorithm.

In this paper are presented current achievements and the state-of-the-art algorithms and implementations for dense linear algebra on traditional architectures such as single-core machines or distributed memory parallel machines. Also, this paper summarizes the current implementations and publicly available libraries for basic linear algebra for mul...