Van Werkhoven B.,Netherlands cience Center |
Hijma P.,VU University Amsterdam
Proceedings - 11th IEEE International Conference on eScience, eScience 2015 | Year: 2015
There are many large scientific applications that have been actively developed for several decades. However, in this time the hardware has evolved considerably. It is taking large scientific applications a very long time to get adjusted to the new computing infrastructure. This is because porting these applications to new hardware, such as Graphics Processing Units (GPUs), currently requires a huge amount of manual labor, even though the computations are very well suited for GPUs. In this paper we propose an integrated approach to semi-automatically port large long-lived scientific codes to GPUs. We propose a method that considerably reduces the effort required by experienced GPU programmers to port these applications. This approach is supported by a tool that is able to analyze, transform, and translate source code into different programming languages. We evaluate our approach by applying it to the Parallel Ocean Program, a representative, very large, and widely-used scientific application. © 2015 IEEE.
Lonsdale R.,University of Bristol |
Hoyle S.,University of Bristol |
Grey D.T.,University of Bristol |
Ridder L.,University of Bristol |
And 2 more authors.
Biochemistry | Year: 2012
Soluble epoxide hydrolase (sEH) is an enzyme involved in drug metabolism that catalyzes the hydrolysis of epoxides to form their corresponding diols. sEH has a broad substrate range and shows high regio- and enantioselectivity for nucleophilic ring opening by Asp333. Epoxide hydrolases therefore have potential synthetic applications. We have used combined quantum mechanics/molecular mechanics (QM/MM) umbrella sampling molecular dynamics (MD) simulations (at the AM1/CHARMM22 level) and high-level ab initio (SCS-MP2) QM/MM calculations to analyze the reactions, and determinants of selectivity, for two substrates: trans-stilbene oxide (t-SO) and trans-diphenylpropene oxide (t-DPPO). The calculated free energy barriers from the QM/MM (AM1/CHARMM22) umbrella sampling MD simulations show a lower barrier for phenyl attack in t-DPPO, compared with that for benzylic attack, in agreement with experiment. Activation barriers in agreement with experimental rate constants are obtained only with the highest level of QM theory (SCS-MP2) used. Our results show that the selectivity of the ring-opening reaction is influenced by several factors, including proximity to the nucleophile, electronic stabilization of the transition state, and hydrogen bonding to two active site tyrosine residues. The protonation state of His523 during nucleophilic attack has also been investigated, and our results show that the protonated form is most consistent with experimental findings. The work presented here illustrates how determinants of selectivity can be identified from QM/MM simulations. These insights may also provide useful information for the design of novel catalysts for use in the synthesis of enantiopure compounds. © 2012 American Chemical Society.
Spaaks J.H.,University of Amsterdam |
Spaaks J.H.,Netherlands cience Center |
Bouten W.,University of Amsterdam
Hydrology and Earth System Sciences | Year: 2013
In hydrological modeling, model structures are developed in an iterative cycle as more and different types of measurements become available and our understanding of the hillslope or watershed improves. However, with increasing complexity of the model, it becomes more and more difficult to detect which parts of the model are deficient, or which processes should also be incorporated into the model during the next development step. In this study, we first compare two methods (the Shuffled Complex Evolution Metropolis algorithm (SCEM-UA) and the Simultaneous parameter Optimization and Data Assimilation algorithm (SODA)) to calibrate a purposely deficient 3-D hillslope-scale model to error-free, artificially generated measurements. We use a multi-objective approach based on distributed pressure head at the soil-bedrock interface and hillslope-scale discharge and water balance. For these idealized circumstances, SODA's usefulness as a diagnostic methodology is demonstrated by its ability to identify the timing and location of processes that are missing in the model. We show that SODA's state updates provide information that could readily be incorporated into an improved model structure, and that this type of information cannot be gained from parameter estimation methods such as SCEM-UA. We then expand on the SODA result by performing yet another calibration, in which we investigate whether SODA's state updating patterns are still capable of providing insight into model structure deficiencies when there are fewer measurements, which are moreover subject to measurement noise. We conclude that SODA can help guide the discussion between experimentalists and modelers by providing accurate and detailed information on how to improve spatially distributed hydrologic models. © Author(s) 2013.
Sanders M.P.A.,Radboud University Nijmegen |
McGuire R.,BioAxis Research BV |
Roumen L.,VU University Amsterdam |
De Esch I.J.P.,VU University Amsterdam |
And 3 more authors.
MedChemComm | Year: 2012
A pharmacophore describes the arrangement of molecular features a ligand must contain to efficaciously bind a receptor. Pharmacophore models are developed to improve molecular understanding of ligand-protein interactions, and can be used as a tool to identify novel compounds that fulfil the pharmacophore requirements and have a high probability of being biologically active. Protein structure-based pharmacophores (SBPs) derive these molecular features by conversion of protein properties to reciprocal ligand space. Unlike ligand-based pharmacophore models, which require templates of ligands in their bioactive conformation, SBPs do not depend on ligand information. The current review describes the different steps in the construction of SBPs: (i) protein structure preparation, (ii) binding site detection, (iii) pharmacophore feature definition, and (iv) pharmacophore feature selection. We show that the SBP modeling workflow poses different challenges than ligand-based pharmacophore modeling, including the definition of protein pharmacophore features essential for ligand binding. A comprehensive overview of different SBP modeling and screening methods and applications is provided to illustrate that SBPs can be efficiently used for virtual screening, ligand binding mode prediction, and binding site similarity detection. Our review demonstrates that SBPs are valuable tools for hit and lead optimization, compound library design and target hopping, especially in cases where ligand information is scarce. © The Royal Society of Chemistry.
Madougou S.,University of Amsterdam |
Varbanescu A.,University of Amsterdam |
De Laat C.,University of Amsterdam |
Van Nieuwpoort R.,Netherlands cience Center
Parallel Computing | Year: 2016
GPUs are gaining fast adoption as high-performance computing architectures, mainly because of their impressive peak performance. Yet most applications only achieve small fractions of this performance. While both programmers and architects have clear opinions about the causes of this performance gap, finding and quantifying the real problems remains a topic for performance modeling tools. In this paper, we sketch the landscape of modern GPUs' performance limiters and optimization opportunities, and dive into details on modeling attempts for GPU-based systems. We highlight the specific features of the relevant contributions in this field, along with the optimization and design spaces they explore. We further use typical kernel examples with various computation and memory access patterns to assess the efficacy and usability of a set of promising approaches. We conclude that the available GPU performance modeling solutions are very sensitive to applications and platform changes, and require significant efforts for tuning and calibration when new analyses are required. © 2016 Elsevier B.V. All rights reserved.