The ALPS project: open source software for strongly correlated systems

We present the ALPS (Algorithms and Libraries for Physics Simulations) project, an international open source software project to develop libraries and application programs for the simulation of strongly correlated quantum lattice models such as quantum magnets, lattice bosons, and strongly correlated fermion systems. Development is centered on common XML and binary data formats, on libraries to simplify and speed up code development, and on full-featured simulation programs. The programs enable non-experts to start carrying out numerical simulations by providing basic implementations of the important algorithms for quantum lattice models: classical and quantum Monte Carlo (QMC) using non-local updates, extended ensemble simulations, exact and full diagonalization (ED), as well as the density matrix renormalization group (DMRG). The software is available from our web server at http://alps.comp-phys.org.Comment: For full software and introductory turorials see http://alps.comp-phys.or

A posteriori metadata from automated provenance tracking: Integration of AiiDA and TCOD

In order to make results of computational scientific research findable, accessible, interoperable and re-usable, it is necessary to decorate them with standardised metadata. However, there are a number of technical and practical challenges that make this process difficult to achieve in practice. Here the implementation of a protocol is presented to tag crystal structures with their computed properties, without the need of human intervention to curate the data. This protocol leverages the capabilities of AiiDA, an open-source platform to manage and automate scientific computational workflows, and TCOD, an open-access database storing computed materials properties using a well-defined and exhaustive ontology. Based on these, the complete procedure to deposit computed data in the TCOD database is automated. All relevant metadata are extracted from the full provenance information that AiiDA tracks and stores automatically while managing the calculations. Such a protocol also enables reproducibility of scientific data in the field of computational materials science. As a proof of concept, the AiiDA-TCOD interface is used to deposit 170 theoretical structures together with their computed properties and their full provenance graphs, consisting in over 4600 AiiDA nodes

Network simulation using the simulation language for alternate modeling (SLAM 2)

The simulation language for alternate modeling (SLAM 2) is a general purpose language that combines network, discrete event, and continuous modeling capabilities in a single language system. The efficacy of the system's network modeling is examined and discussed. Examples are given of the symbolism that is used, and an example problem and model are derived. The results are discussed in terms of the ease of programming, special features, and system limitations. The system offers many features which allow rapid model development and provides an informative standardized output. The system also has limitations which may cause undetected errors and misleading reports unless the user is aware of these programming characteristics

Racing to hardware-validated simulation

Processor simulators rely on detailed timing models of the processor pipeline to evaluate performance. The diversity in real-world processor designs mandates building flexible simulators that expose parts of the underlying model to the user in the form of configurable parameters. Consequently, the accuracy of modeling a real processor relies on both the accuracy of the pipeline model itself, and the accuracy of adjusting the configuration parameters according to the modeled processor. Unfortunately, processor vendors publicly disclose only a subset of their design decisions, raising the probability of introducing specification inaccuracies when modeling these processors. Inaccurately tuning model parameters deviates the simulated processor from the actual one. In the worst case, using improper parameters may lead to imbalanced pipeline models compromising the simulation output. Therefore, simulation models should be hardware-validated before using them for performance evaluation. As processors increase in complexity and diversity, validating a simulator model against real hardware becomes increasingly more challenging and time-consuming. In this work, we propose a methodology for validating simulation models against real hardware. We create a framework that relies on micro-benchmarks to collect performance statistics on real hardware, and machine learning-based algorithms to fine-tune the unknown parameters based on the accumulated statistics. We overhaul the Sniper simulator to support the ARM AArch64 instruction-set architecture (ISA), and introduce two new timing models for ARM-based in-order and out-of-order cores. Using our proposed simulator validation framework, we tune the in-order and out-of-order models to match the performance of a real-world implementation of the Cortex-A53 and Cortex-A72 cores with an average error of 7% and 15%, respectively, across a set of SPEC CPU2017 benchmarks

Spin-orbit coupled j=1/2 iridium moments on the geometrically frustrated fcc lattice

Motivated by experiments on the double perovskites La2ZnIrO6 and La2MgIrO6, we study the magnetism of spin-orbit coupled j=1/2 iridium moments on the three-dimensional, geometrically frustrated, face-centered cubic lattice. The symmetry-allowed nearest-neighbor interaction includes Heisenberg, Kitaev, and symmetric off-diagonal exchange. A Luttinger-Tisza analysis shows a rich variety of orders, including collinear A-type antiferromagnetism, stripe order with moments along the [111]-direction, and incommensurate non-coplanar spirals, and we use Monte Carlo simulations to determine their magnetic ordering temperatures. We argue that existing thermodynamic data on these iridates underscores the presence of a dominant Kitaev exchange, and also suggest a resolution to the puzzle of why La2ZnIrO6 exhibits `weak' ferromagnetism, but La2MgIrO6 does not.Comment: 5 pages, 5 figs, significantly revised to address referee comments, to appear in PRB Rapid Com