Finite-volume Hamiltonian method for coupled channel interactions in lattice QCD

Within a multi-channel formulation of $\pi\pi$ scattering, we investigate the use of the finite-volume Hamiltonian approach to resolve scattering observables from lattice QCD spectra. The asymptotic matching of the well-known L\"uscher formalism encodes a unique finite-volume spectrum. Nevertheless, in many practical situations, such as coupled-channel systems, it is advantageous to interpolate isolated lattice spectra in order to extract physical scattering parameters. Here we study the use of the Hamiltonian framework as a parameterisation that can be fit directly to lattice spectra. We find that with a modest amount of lattice data, the scattering parameters can be reproduced rather well, with only a minor degree of model dependence.Comment: 25 pages, 16 figure

Electronic structure and bonding properties of cobalt oxide in the spinel structure

The spinel cobalt oxide Co3O4 is a magnetic semiconductor containing cobalt ions in Co2+ and Co3+ oxidation states. We have studied the electronic, magnetic and bonding properties of Co3O4 using density functional theory (DFT) at the Generalized Gradient Approximation (GGA), GGA+U, and PBE0 hybrid functional levels. The GGA correctly predicts Co3O4 to be a semiconductor, but severely underestimates the band gap. The GGA+U band gap (1.96 eV) agrees well with the available experimental value (~ 1.6 eV), whereas the band gap obtained using the PBE0 hybrid functional (3.42 eV) is strongly overestimated. All the employed exchange-correlation functionals predict 3 unpaired d electrons on the Co2+ ions, in agreement with crystal field theory, but the values of the magnetic moments given by GGA+U and PBE0 are in closer agreement with the experiment than the GGA value, indicating a better description of the cobalt localized d states. Bonding properties are studied by means of Maximally Localized Wannier Functions (MLWFs). We find d-type MLWFs on the cobalt ions, as well as Wannier functions with the character of sp3d bonds between cobalt and oxygen ions. Such hybridized bonding states indicate the presence of a small covalent component in the primarily ionic bonding mechanism of this compound.Comment: 24 pages, 8 figure

The CJT calculation in studying nuclear matter beyond mean field approximation

We have introduced a CJT calculation in studying nuclear matter beyond mean field approximation. Based on the CJT formalism and using Walecka model, we have derived a set of coupled Dyson equations of nucleons and mesons. Neglecting the medium effects of the mesons, the usual MFT results could be reproduced. The beyond MFT calculations have been performed by thermodynamic consistently determining the meson effective masses and solving the coupled gap equations for nucleons and mesons. The numerical results for the nucleon and meson effective masses at finite temperature and chemical potential in nuclear matter are discussed.Comment: 8 pages, 8 figure

Gunrock: A High-Performance Graph Processing Library on the GPU

For large-scale graph analytics on the GPU, the irregularity of data access and control flow, and the complexity of programming GPUs have been two significant challenges for developing a programmable high-performance graph library. "Gunrock", our graph-processing system designed specifically for the GPU, uses a high-level, bulk-synchronous, data-centric abstraction focused on operations on a vertex or edge frontier. Gunrock achieves a balance between performance and expressiveness by coupling high performance GPU computing primitives and optimization strategies with a high-level programming model that allows programmers to quickly develop new graph primitives with small code size and minimal GPU programming knowledge. We evaluate Gunrock on five key graph primitives and show that Gunrock has on average at least an order of magnitude speedup over Boost and PowerGraph, comparable performance to the fastest GPU hardwired primitives, and better performance than any other GPU high-level graph library.Comment: 14 pages, accepted by PPoPP'16 (removed the text repetition in the previous version v5

Electronic structure and Jahn-Teller effect in GaN:Mn and ZnS:Cr

We present an ab-initio and analytical study of the Jahn-Teller effect in two diluted magnetic semiconductors (DMS) with d4 impurities, namely Mn-doped GaN and Cr-doped ZnS. We show that only the combined treatment of Jahn-Teller distortion and strong electron correlation in the 3d shell may lead to the correct insulating electronic structure. Using the LSDA+U approach we obtain the Jahn-Teller energy gain in reasonable agreement with the available experimental data. The ab-initio results are completed by a more phenomenological ligand field theory.Comment: 15 pages, 5 figure

Optimized Broadcast for Deep Learning Workloads on Dense-GPU InfiniBand Clusters: MPI or NCCL?

Dense Multi-GPU systems have recently gained a lot of attention in the HPC arena. Traditionally, MPI runtimes have been primarily designed for clusters with a large number of nodes. However, with the advent of MPI+CUDA applications and CUDA-Aware MPI runtimes like MVAPICH2 and OpenMPI, it has become important to address efficient communication schemes for such dense Multi-GPU nodes. This coupled with new application workloads brought forward by Deep Learning frameworks like Caffe and Microsoft CNTK pose additional design constraints due to very large message communication of GPU buffers during the training phase. In this context, special-purpose libraries like NVIDIA NCCL have been proposed for GPU-based collective communication on dense GPU systems. In this paper, we propose a pipelined chain (ring) design for the MPI_Bcast collective operation along with an enhanced collective tuning framework in MVAPICH2-GDR that enables efficient intra-/inter-node multi-GPU communication. We present an in-depth performance landscape for the proposed MPI_Bcast schemes along with a comparative analysis of NVIDIA NCCL Broadcast and NCCL-based MPI_Bcast. The proposed designs for MVAPICH2-GDR enable up to 14X and 16.6X improvement, compared to NCCL-based solutions, for intra- and inter-node broadcast latency, respectively. In addition, the proposed designs provide up to 7% improvement over NCCL-based solutions for data parallel training of the VGG network on 128 GPUs using Microsoft CNTK.Comment: 8 pages, 3 figure

Relaxed 2-D Principal Component Analysis by LpL_p Norm for Face Recognition

A relaxed two dimensional principal component analysis (R2DPCA) approach is proposed for face recognition. Different to the 2DPCA, 2DPCA-$L_1$ and G2DPCA, the R2DPCA utilizes the label information (if known) of training samples to calculate a relaxation vector and presents a weight to each subset of training data. A new relaxed scatter matrix is defined and the computed projection axes are able to increase the accuracy of face recognition. The optimal $L_p$-norms are selected in a reasonable range. Numerical experiments on practical face databased indicate that the R2DPCA has high generalization ability and can achieve a higher recognition rate than state-of-the-art methods.Comment: 19 pages, 11 figure

The NN phase shifts in the extended quark-delocalization, color-screening model

An alternative method is applied to the study of nucleon-nucleon(NN) scattering phase shifts in the framework of extended quark delocalization, color-screening model(QDCSM), where the one-pion-exchange(OPE) with short-range cutoff is included.Comment: 5 pages, 3 figures, two-colum