Universal and nonuniversal contributions to block-block entanglement in many-fermion systems

We calculate the entanglement entropy of blocks of size x embedded in a larger system of size L, by means of a combination of analytical and numerical techniques. The complete entanglement entropy in this case is a sum of three terms. One is a universal x- and L-dependent term, first predicted by Calabrese and Cardy, the second is a nonuniversal term arising from the thermodynamic limit, and the third is a finite size correction. We give an explicit expression for the second, nonuniversal, term for the one-dimensional Hubbard model, and numerically assess the importance of all three contributions by comparing to the entropy obtained from fully numerical diagonalization of the many-body Hamiltonian. We find that finite-size corrections are very small. The universal Calabrese-Cardy term is equally small for small blocks, but becomes larger for x > 1. In all investigated situations, however, the by far dominating contribution is the nonuniversal term stemming from the thermodynamic limit.

Entanglement in spatially inhomogeneous many-fermion systems

We investigate entanglement of strongly interacting fermions in spatially inhomogeneous environments. To quantify entanglement in the presence of spatial inhomogeneity, we propose a local-density approximation (LDA) to the entanglement entropy, and a nested LDA scheme to evaluate the entanglement entropy on inhomogeneous density profiles. These ideas are applied to models of electrons in superlattice structures with different modulation patterns, electrons in a metallic wire in the presence of impurities, and phase-separated states in harmonically confined many-fermion systems, such as electrons in quantum dots and atoms in optical traps. We find that the entanglement entropy of inhomogeneous systems is strikingly different from that of homogeneous systems.

Reverse engineering in many-body quantum physics: Correspondence between many-body systems and effective single-particle equations

The mapping, exact or approximate, of a many-body problem onto an effective single-body problem is one of the most widely used conceptual and computational tools of physics. Here, we propose and investigate the inverse map of effective approximate single-particle equations onto the corresponding many-particle system. This approach allows us to understand which interacting system a given single-particle approximation is actually describing, and how far this is from the original physical many-body system. We illustrate the resulting reverse engineering process by means of the Kohn-Sham equations of density-functional theory. In this application, our procedure sheds light on the nonlocality of the density-potential mapping of density-functional theory, and on the self-interaction error inherent in approximate density functionals.

Algorithm-oriented design of efficient many-core architectures applied to dense matrix multiplication

Recent integrated circuit technologies have opened the possibility to design parallel architectures with hundreds of cores on a single chip. The design space of these parallel architectures is huge with many architectural options. Exploring the design space gets even more difficult if, beyond performance and area, we also consider extra metrics like performance and area efficiency, where the designer tries to design the architecture with the best performance per chip area and the best sustainable performance. In this paper we present an algorithm-oriented approach to design a many-core architecture. Instead of doing the design space exploration of the many core architecture based on the experimental execution results of a particular benchmark of algorithms, our approach is to make a formal analysis of the algorithms considering the main architectural aspects and to determine how each particular architectural aspect is related to the performance of the architecture when running an algorithm or set of algorithms. The architectural aspects considered include the number of cores, the local memory available in each core, the communication bandwidth between the many-core architecture and the external memory and the memory hierarchy. To exemplify the approach we did a theoretical analysis of a dense matrix multiplication algorithm and determined an equation that relates the number of execution cycles with the architectural parameters. Based on this equation a many-core architecture has been designed. The results obtained indicate that a 100 mm(2) integrated circuit design of the proposed architecture, using a 65 nm technology, is able to achieve 464 GFLOPs (double precision floating-point) for a memory bandwidth of 16 GB/s. This corresponds to a performance efficiency of 71 %. Considering a 45 nm technology, a 100 mm(2) chip attains 833 GFLOPs which corresponds to 84 % of peak performance These figures are better than those obtained by previous many-core architectures, except for the area efficiency which is limited by the lower memory bandwidth considered. The results achieved are also better than those of previous state-of-the-art many-cores architectures designed specifically to achieve high performance for matrix multiplication.

Sparse matrix multiplication on a reconfigurable many-core architecture

Sparse matrix-vector multiplication (SMVM) is a fundamental operation in many scientific and engineering applications. In many cases sparse matrices have thousands of rows and columns where most of the entries are zero, while non-zero data is spread over the matrix. This sparsity of data locality reduces the effectiveness of data cache in general-purpose processors quite reducing their performance efficiency when compared to what is achieved with dense matrix multiplication. In this paper, we propose a parallel processing solution for SMVM in a many-core architecture. The architecture is tested with known benchmarks using a ZYNQ-7020 FPGA. The architecture is scalable in the number of core elements and limited only by the available memory bandwidth. It achieves performance efficiencies up to almost 70% and better performances than previous FPGA designs.

Real-Time Application Mapping for Many-Cores Using a Limited Migrative Model

Many-core platforms are an emerging technology in the real-time embedded domain. These devices offer various options for power savings, cost reductions and contribute to the overall system flexibility, however, issues such as unpredictability, scalability and analysis pessimism are serious challenges to their integration into the aforementioned area. The focus of this work is on many-core platforms using a limited migrative model (LMM). LMM is an approach based on the fundamental concepts of the multi-kernel paradigm, which is a promising step towards scalable and predictable many-cores. In this work, we formulate the problem of real-time application mapping on a many-core platform using LMM, and propose a three-stage method to solve it. An extended version of the existing analysis is used to assure that derived mappings (i) guarantee the fulfilment of timing constraints posed on worst-case communication delays of individual applications, and (ii) provide an environment to perform load balancing for e.g. energy/thermal management, fault tolerance and/or performance reasons.

Methodologies for the WCET Analysis of Parallel Applications on Many-core Architectures

Euromicro Conference on Digital System Design (DSD 2015), Funchal, Portugal.

Partitioning the Network-on-Chip to Enable Virtualization on Many-Core Processors

6th International Real-Time Scheduling Open Problems Seminar (RTSOPS 2015), Lund, Sweden.

Real-time Parallel Applications on Many-core Architectures

Presented at INForum - Simpósio de Informática (INFORUM 2015). 7 to 8, Sep, 2015. Portugal.

Embedded Multi-Core systems for Mixed Criticality applications in dynamic and changeable real-time environments

EMC2 finds solutions for dynamic adaptability in open systems. It provides handling of mixed criticality multicore applications in r eal-time conditions, withscalability and utmost flexibility, full-scale deployment and management of integrated tool chains, through the entire lifecycle.

Optimització d'una aplicació bioinformàtica d'aliniament de seqüències executada en processadors many-core (GPUs)

Las herramientas de análisis de secuencias genómicas permiten a los biólogos identificar y entender regiones fundamentales que tienen implicación en enfermedades genéticas. Actualmente existe una necesidad de dotar al ámbito científico de herramientas de análisis eficientes. Este proyecto lleva a cabo una caracterización y análisis del rendimiento de algoritmos utilizados en la comparación de secuencias genómicas completas, y ejecutadas en arquitecturas MultiCore y ManyCore. A partir del análisis se evalúa la idoneidad de este tipo de arquitecturas para resolver el problema de comparar secuencias genómicas. Finalmente se propone una serie de modificaciones en las implementaciones de estos algoritmos con el objetivo de mejorar el rendimiento.

Delta(1232) isobar excitations in nuclear many-body systems from varios NN interactions.

Delta isobar components in the nuclear many-body wave function are investigated for the deuteron, light nuclei (16O), and infinite nuclear matter within the framework of the coupled-cluster theory. The predictions derived for various realistic models of the baryon-baryon interaction are compared to each other. These include local (V28) and nonlocal meson exchange potentials (Bonn2000) but also a model recently derived by the Salamanca group accounting for quark degrees of freedom. The characteristic differences which are obtained for the NDelta and Delta Delta correlation functions are related to the approximation made in deriving the matrix elements for the baryon-baryon interaction.

Dielectric formulation for Many-Particle Systems with General Interactions

An extension of the self-consistent field approach formulation by Cohen in the preceding paper is proposed in order to include the most general kind of two-body interactions, i.e., interactions depending on position, momenta, spin, isotopic spin, etc. The dielectric function is replaced by a dielectric matrix. The evaluation of the energies involves the computation of a matrix inversion and trace.

Delta(1232) isobar excitations in nuclear many-body systems from varios NN interactions.

Delta isobar components in the nuclear many-body wave function are investigated for the deuteron, light nuclei (16O), and infinite nuclear matter within the framework of the coupled-cluster theory. The predictions derived for various realistic models of the baryon-baryon interaction are compared to each other. These include local (V28) and nonlocal meson exchange potentials (Bonn2000) but also a model recently derived by the Salamanca group accounting for quark degrees of freedom. The characteristic differences which are obtained for the NDelta and Delta Delta correlation functions are related to the approximation made in deriving the matrix elements for the baryon-baryon interaction.