Accelerating scientific applications on GPUs

We have analyzed and accelerated two large scientific applications used at the Barcelona Supercomputer Center (BSC). With this, we want to show how two complex applications can be efficiently ported to GPUs. In addition, we have developed a mechanism to manage the coherency of CPU/GPU memories

Implementació del suport OpenCL sobre GMAC

[CATALÀ] El projecte consisteix en realitzar el back-end d'OpenCL per a GMAC, basant-se en el back-end de CUDA que ja es troba en funcionament. Realitzar els diversos tests que actualment comproven que el back-end de CUDA funciona, i comprovar que el back-end d'OpenCL 'es equivalent en rendiment al de CUD[ANGLÈS] The project is to perform the back-end of OpenCL for the run-time GMAC, based on the CUDA backend which is already in operation. Perform various tests that currently check the CUDA backend, and check the back-end performance is equivalent to CUDA

Probing Long-Range Interactions by Extracting Free Energies From Genome-Wide Chromosome Conformation Capture Data

Background A variety of DNA binding proteins are involved in regulating and shaping the packing of chromatin. They aid the formation of loops in the DNA that function to isolate different structural domains. A recent experimental technique, Hi-C, provides a method for determining the frequency of such looping between all distant parts of the genome. Given that the binding locations of many chromatin associated proteins have also been measured, it has been possible to make estimates for their influence on the long-range interactions as measured by Hi-C. However, a challenge in this analysis is the predominance of non-specific contacts that mask out the specific interactions of interest. Results We show that transforming the Hi-C contact frequencies into free energies gives a natural method for separating out the distance dependent non-specific interactions. In particular we apply Principal Component Analysis (PCA) to the transformed free energy matrix to identify the dominant modes of interaction. PCA identifies systematic effects as well as high frequency spatial noise in the Hi-C data which can be filtered out. Thus it can be used as a data driven approach for normalizing Hi-C data. We assess this PCA based normalization approach, along with several other normalization schemes, by fitting the transformed Hi-C data using a pairwise interaction model that takes as input the known locations of bound chromatin factors. The result of fitting is a set of predictions for the coupling energies between the various chromatin factors and their effect on the energetics of looping. We show that the quality of the fit can be used as a means to determine how much PCA filtering should be applied to the Hi-C data. Conclusions We find that the different normalizations of the Hi-C data vary in the quality of fit to the pairwise interaction model. PCA filtering can improve the fit, and the predicted coupling energies lead to biologically meaningful insights for how various chromatin bound factors influence the stability of DNA loops in chromatin

Evaluating directive-based programming models on Wave Propagation Kernels

HPC systems have become mandatory to tackle the ever-increasing challenges imposed by new exploration areas around the world. The requirement for more HPC resources depends on the complexity of the area under exploration, yet the larger the HPC system, the more the energy consumption involved. Reduction of overall power consumption in HPC facilities, lead technologies vendors to introduce many-core devices and heterogeneous computing to the supercomputers, thus, forcing exploration codes to be ported to such new architectures. As the Oil & Gas industry has more than 30 years of legacy code, the effort to adapt it could be huge. To this extent, several programming models emerged, e.g. high-level directive-based programming models, such as OpenMP, OpenACC, and OmpSs rely on specifying to the compiler the parallelism directives to release users from manually decomposing and processing the parallel regions. The results show that it is possible to obtain a parallel code for current heterogeneous HPC architectures investing a few hours or days. The obtained speedup is at least an order of magnitude w.r.t. a sequential code. However, we provide parallelism inside a single computational node, and a wider study for evaluating the costs of porting and parallelizing across computational nodes is pending.Authors thank Repsol for the permission to publish the present research, carried out at the Repsol-BSC Research Center. This work has received funding from the European Union’s Horizon 2020 Programme (2014-2020) and from the Brazilian Ministry of Science, Technology and Innovation through Rede Nacional de Pesquisa (RNP) under the HPC4E Project (www.hpc4e.eu), grant agreement n.◦ 689772.Peer ReviewedPostprint (author's final draft

Design of a simpler ampere-hourmeter

In any application in which working with batteries is a must, the knowledge of the batteries’ state-of-charge (SOC) is a fundamental parameter for anyone, so it determines the remaining capacity in the battery. There exist several methods for the estimation of this SOC in Lead-acid batteries; however, when the requisites of the measuring method must offer, besides precision and reliability, the possibility to integrate the results into an automatized system, the Coulomb’s counter is the method that prevails. This paper presents, then, the design of a simpler Ampere-hourmeter based lead-acid battery SOC estimating system. Supported by previous studies in the field of SOC estimation in Hybrid Electric Vehicles and by experimental tests carried out by the researchers, the modelling of the simpler measuring system has been parameterized by following Peukert’s Equation, and afterwards it has been integrated into a data acquisition and processing system designed through a CSNX25 current sensor and a low-cost and low-consume 16F877 microcontroller. The fundamental conclusion of this paper is that obtaining an accurate result while estimating the SOC of a lead-acid battery with an simpler Ampere-hourmeter developed through a microcontroller based system is achievable but only if the used microcontroller holds enough memory to include the whole data treatment algorithms.Peer ReviewedPostprint (published version

Dense Neural Networks for Predicting Chromatin Conformation

Background  DNA inside eukaryotic cells wraps around histones to form the 11nm chromatin fiber that can further fold into higher-order DNA loops, which may depend on the binding of architectural factors. Predicting how the DNA will fold given a distribution of bound factors, here viewed as a type of sequence, is currently an unsolved problem and several heterogeneous polymer models have shown that many features of the measured structure can be reproduced from simulations. However a model that determines the optimal connection between sequence and structure and that can rapidly assess the effects of varying either one is still lacking. Results  Here we train a dense neural network to solve for the local folding of chromatin, connecting structure, represented as a contact map, to a sequence of bound chromatin factors. The network includes a convolutional filter that compresses the large number of bound chromatin factors into a single 1D sequence representation that is optimized for predicting structure. We also train a network to solve the inverse problem, namely given only structural information in the form of a contact map, predict the likely sequence of chromatin states that generated it. Conclusions  By carrying out sensitivity analysis on both networks, we are able to highlight the importance of chromatin contexts and neighborhoods for regulating long-range contacts, along with critical alterations that affect contact formation. Our analysis shows that the networks have learned physical insights that are informative and intuitive about this complex polymer problem

A Maximum-Entropy Model for Predicting Chromatin Contacts

The packaging of DNA inside a nucleus shows complex structure stabilized by a host of DNA-bound factors. Both the distribution of these factors and the contacts between different genomic locations of the DNA can now be measured on a genome-wide scale. This has advanced the development of models aimed at predicting the conformation of DNA given only the locations of bound factors—the chromatin folding problem. Here we present a maximum-entropy model that is able to predict a contact map representation of structure given a sequence of bound factors. Non-local effects due to the sequence neighborhood around contacting sites are found to be important for making accurate predictions. Lastly, we show that the model can be used to infer a sequence of bound factors given only a measurement of structure. This opens up the possibility for efficiently predicting sequence regions that may play a role in generating cell-type specific structural differences

Optimization of atmospheric transport models on HPC platforms

The performance and scalability of atmospheric transport models on high performance computing environments is often far from optimal for multiple reasons including, for example, sequential input and output, synchronous communications, work unbalance, memory access latency or lack of task overlapping. We investigate how different software optimizations and porting to non general-purpose hardware architectures improve code scalability and execution times considering, as an example, the FALL3D volcanic ash transport model. To this purpose, we implement the FALL3D model equations in the WARIS framework, a software designed from scratch to solve in a parallel and efficient way different geoscience problems on a wide variety of architectures. In addition, we consider further improvements in WARIS such as hybrid MPI-OMP parallelization, spatial blocking, auto-tuning and thread affinity. Considering all these aspects together, the FALL3D execution times for a realistic test case running on general-purpose cluster architectures (Intel Sandy Bridge) decrease by a factor between 7 and 40 depending on the grid resolution. Finally, we port the application to Intel Xeon Phi (MIC) and NVIDIA GPUs (CUDA) accelerator-based architectures and compare performance, cost and power consumption on all the architectures. Implications on time-constrained operational model configurations are discussed.We thank M.S. Osores from the Argentinean National Scientific and Technical Research Council (CONICET) for providing hourly column heights for the Cordón Caulle eruption simulation and the constructive comments from two anonymous reviewers. This work was supported by NVIDIA through the UPC/BSC GPU Center of Excellence, and the Spanish Ministry of Science and Technology through the TIN2012-34557 project. Finally, we dedicate this work to our colleague and co-author Nacho Navarro, who sadly passed away during the reviewing process.Peer ReviewedPostprint (author's final draft

Experimental validation of the adiabatic assumption of short-circuit tests on bare conductors

©2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.According to various international standards, many high-voltage devices must withstand short-circuit tests. Due to the enormous power and current requirements, they have to be tested in very specialized and expensive power laboratories, which are scarce and not affordable for the vast majority of electrical product manufacturers. It is proposed to break the time limit of about one second imposed by the standards by using a lower current to heat for a longer time, requiring more affordable equipment and thus reducing the cost for testing. This work analyzes the limits of the adiabatic assumption in short-circuit tests in order to quantify how the duration of these tests can be extended to reduce the power required and the current applied, while obtaining almost the same results, i.e., the same temperature at the end of the heating phase of the tests. For this purpose, bare cylindrical conductors are analyzed and the temperature dependence of the properties of the conductor material is considered. Experimental and simulation results presented in this paper suggest that by applying this approach, short-circuit tests intended for product design, verification and quality control can be performed in much less demanding and affordable laboratory facilities.This work was supported in part by the by Ministerio de Ciencia e Innovación de España, grant number PID2020-114240RB-I00 and by the Generalitat de Catalunya, grant number 2021 SGR 00392.Peer ReviewedPostprint (author's final draft