An update on the BQCD Hybrid Monte Carlo program

We present an update of BQCD, our Hybrid Monte Carlo program for simulating lattice QCD. BQCD is one of the main production codes of the QCDSF collaboration and is used by CSSM and in some Japanese finite temperature and finite density projects. Since the first publication of the code at Lattice 2010 the program has been extended in various ways. New features of the code include: dynamical QED, action modification in order to compute matrix elements by using Feynman-Hellman theory, more trace measurements, a more flexible integration scheme, polynomial filtering, term-splitting for RHMC, and a portable implementation of performance critical parts employing SIMD.Comment: Poster presented at the 35th International Symposium on Lattice Field Theory, Granada, Spain, 18-24 June 201

Nucleon distribution amplitudes from lattice QCD

We calculate low moments of the leading-twist and next-to-leading twist nucleon distribution amplitudes on the lattice using two flavors of clover fermions. The results are presented in the MSbar scheme at a scale of 2 GeV and can be immediately applied in phenomenological studies. We find that the deviation of the leading-twist nucleon distribution amplitude from its asymptotic form is less pronounced than sometimes claimed in the literature.Comment: 5 pages, 3 figures, 2 tables. RevTeX style. Normalization for \lambda_i corrected. Discussion of the results extended. To be published in PR

Towards an HPC certification program

The HPC community has always considered the training of new and existing HPC practitioners to be of high importance to its growth. This diversification of HPC practitioners challenges the traditional training approaches, which are not able to satisfy the specific needs of users, often coming from non-traditionally HPC disciplines, and only interested in learning a particular set of competences. Challenges for HPC centres are to identify and overcome the gaps in users’ knowledge, while users struggle to identify relevant skills. We have developed a first version of an HPC certification program that would clearly categorize, define, and examine competences. Making clear what skills are required of or recommended for a competent HPC user would benefit both the HPC service providers and practitioners. Moreover, it would allow centres to bundle together skills that are most beneficial for specific user roles and scientific domains. From the perspective of content providers, existing training material can be mapped to competences allowing users to quickly identify and learn the skills they require. Finally, the certificates recognized by the whole HPC community simplify inter-comparison of independently offered courses and provide additional incentive for participation

Non-perturbative renormalization of three-quark operators

High luminosity accelerators have greatly increased the interest in semi-exclusive and exclusive reactions involving nucleons. The relevant theoretical information is contained in the nucleon wavefunction and can be parametrized by moments of the nucleon distribution amplitudes, which in turn are linked to matrix elements of local three-quark operators. These can be calculated from first principles in lattice QCD. Defining an RI-MOM renormalization scheme, we renormalize three-quark operators corresponding to low moments non-perturbatively and take special care of the operator mixing. After performing a scheme matching and a conversion of the renormalization scale we quote our final results in the MSbar scheme at mu=2 GeV.Comment: 49 pages, 3 figure

Vectorization and Parallelization of Irregular Problems via Graph Coloring

Efficient implementations of irregular problems on vector and parallel architectures generally are hard to realize. An important class of irregular problems are Gau-Seidel iteration schemes applied to irregular data sets. The unstructured data dependences arising there prevent restructuring compilers from generating efficient code for vector or parallel machines. It is shown, how to structure the data dependences by decomposing the data set using graph coloring techniques and by specifying a particular execution order already on the algorithm level. Methods to master the irregularities originating from different types of tasks are proposed. An example of application is given and possible future developments are mentioned. Contents 1 Introduction 1 2 Preliminaries 2 2.1 Graphs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 2.2 Data Dependences . . . . . . . . . . . . . . . . . . . . . . . . 3 3 Iteration Schemes 4 4 Gau-Seidel Iterations for Regular Problems 6 5 Ga..