arXiv subjects

Matthew D. Jones

Publications and source records attributed to Matthew D. Jones.

10 recordsLinked to original sources

arXiv2025

Standardizing Intelligence: Aligning Generative AI for Regulatory and Operational Compliance

Technical standards, or simply standards, are established documented guidelines and rules that facilitate the interoperability, quality, and accuracy of systems and processes. In recent years, we have witnessed an emerging paradigm shift where the adoption of generative AI (GenAI) models has increased tremendously, spreading implementation interests across standard-driven industries, including engineering, legal, healthcare, and education. In this paper, we assess the criticality levels of different standards across domains and sectors and complement them by grading the current compliance capabilities of state-of-the-art GenAI models. To support the discussion, we outline possible challenges and opportunities with integrating GenAI for standard compliance tasks while also providing actionable recommendations for entities involved with developing and using standards. Overall, we argue that aligning GenAI with standards through computational methods can help strengthen regulatory and operational compliance. We anticipate this area of research will play a central role in the management, oversight, and trustworthiness of larger, more powerful GenAI-based systems in the near future.

cs.CY↗

arXiv2019

Modernizing Titan2D, a Parallel AMR Geophysical Flow Code to Support Multiple Rheologies and Extendability

In this work, we report on strategies and results of our initial approach for modernization of Titan2D code. Titan2D is a geophysical mass flow simulation code designed for modeling of volcanic flows, debris avalanches and landslides over a realistic terrain model. It solves an underlying hyperbolic system of partial differential equations using parallel adaptive mesh Godunov scheme. The following work was done during code refactoring and modernization. To facilitate user input two level python interface was developed. Such design permits large changes in C++ and Python low-level while maintaining stable high-level interface exposed to the end user. Multiple diverged forks implementing different material models were merged back together. Data storage layout was changed from a linked list of structures to a structure of arrays representation for better memory access and in preparation for further work on better utilization of vectorized instruction. Existing MPI parallelization was augmented with OpenMP parallelization. The performance of a hash table used to store mesh elements and nodes references was improved by switching from a linked list for overflow entries to dynamic arrays allowing the implementation of the binary search algorithm. The introduction of the new data layout made possible to reduce the number of hash table look-ups by replacing them with direct use of indexes from the storage class. The modifications lead to 8-9 times performance improvement for serial execution.

physics.comp-ph↗

arXiv2019

Reconfiguration of Connected Graph Partitions

Motivated by recent computational models for redistricting and detection of gerrymandering, we study the following problem on graph partitions. Given a graph $G$ and an integer $k\geq 1$, a $k$-district map of $G$ is a partition of $V(G)$ into $k$ nonempty subsets, called districts, each of which induces a connected subgraph of $G$. A switch is an operation that modifies a $k$-district map by reassigning a subset of vertices from one district to an adjacent district; a 1-switch is a switch that moves a single vertex. We study the connectivity of the configuration space of all $k$-district maps of a graph $G$ under 1-switch operations. We give a combinatorial characterization for the connectedness of this space that can be tested efficiently. We prove that it is NP-complete to decide whether there exists a sequence of 1-switches that takes a given $k$-district map into another; and NP-hard to find the shortest such sequence (even if a sequence of polynomial length is known to exist). We also present efficient algorithms for computing a sequence of 1-switches that takes a given $k$-district map into another when the space is connected, and show that these algorithms perform a worst-case optimal number of switches up to constant factors.

cs.DM↗

arXiv2018

Maximum Area Axis-Aligned Square Packings

Given a point set $S=\{s_1,\ldots , s_n\}$ in the unit square $U=[0,1]^2$, an anchored square packing is a set of $n$ interior-disjoint empty squares in $U$ such that $s_i$ is a corner of the $i$th square. The reach $R(S)$ of $S$ is the set of points that may be covered by such a packing, that is, the union of all empty squares anchored at points in $S$. It is shown that area$(R(S))\geq \frac12$ for every finite set $S\subset U$, and this bound is the best possible. The region $R(S)$ can be computed in $O(n\log n)$ time. Finally, we prove that finding a maximum area anchored square packing is NP-complete. This is the first hardness proof for a geometric packing problem where the size of geometric objects in the packing is unrestricted.

cs.CG↗

arXiv2018

Effect of Meltdown and Spectre Patches on the Performance of HPC Applications

In this work we examine how the updates addressing Meltdown and Spectre vulnerabilities impact the performance of HPC applications. To study this we use the application kernel module of XDMoD to test the performance before and after the application of the vulnerability patches. We tested the performance difference for multiple application and benchmarks including: NWChem, NAMD, HPCC, IOR, MDTest and IMB. The results show that although some specific functions can have performance decreased by as much as 74%, the majority of individual metrics indicates little to no decrease in performance. The real-world applications show a 2-3% decrease in performance for single node jobs and a 5-11% decrease for parallel multi node jobs.

cs.PF↗

arXiv2018

A Workload Analysis of NSF's Innovative HPC Resources Using XDMoD

Workload characterization is an integral part of performance analysis of high performance computing (HPC) systems. An understanding of workload properties sheds light on resource utilization and can be used to inform performance optimization both at the software and system configuration levels. It can provide information on how computational science usage modalities are changing that could potentially aid holistic capacity planning for the wider HPC ecosystem. Here, we report on the results of a detailed workload analysis of the portfolio of supercomputers comprising the NSF Innovative HPC program in order to characterize its past and current workload and look for trends to understand the nature of how the broad portfolio of computational science research is being supported and how it is changing over time. The workload analysis also sought to illustrate a wide variety of usage patterns and performance requirements for jobs running on these systems. File system performance, memory utilization and the types of parallelism employed by users (MPI, threads, etc) were also studied for all systems for which job level performance data was available.

cs.DC↗

arXiv2017

Workload Analysis of Blue Waters

Blue Waters is a Petascale-level supercomputer whose mission is to enable the national scientific and research community to solve "grand challenge" problems that are orders of magnitude more complex than can be carried out on other high performance computing systems. Given the important and unique role that Blue Waters plays in the U.S. research portfolio, it is important to have a detailed understanding of its workload in order to guide performance optimization both at the software and system configuration level as well as inform architectural balance tradeoffs. Furthermore, understanding the computing requirements of the Blue Water's workload (memory access, IO, communication, etc.), which is comprised of some of the most computationally demanding scientific problems, will help drive changes in future computing architectures, especially at the leading edge. With this objective in mind, the project team carried out a detailed workload analysis of Blue Waters.

cs.DC↗

arXiv2014

Versatile Cold Atom Source for Multi-Species Experiments

We present a dual-species oven and Zeeman slower setup capable of producing slow, high-flux atomic beams for loading magneto-optical traps. Our compact and versatile system is based on electronic switching between different magnetic field profiles and is applicable to a wide range of multi-species experiments. We give details of the vacuum setup, coils and simple electronic circuitry. In addition, we demonstrate the performance of our system by optimized, sequential loading of magneto-optical traps of lithium-6 and cesium-133.

physics.atom-ph↗

arXiv2002

Block-Diagonalization and f-electron Effects in Tight-Binding Theory

We extend a tight-binding total energy method to include f-electrons, and apply it to the study of the structural and elastic properties of a range of elements from Be to U. We find that the tight-binding parameters are as accurate and transferable for f-electron systems as they are for d-electron systems. In both cases we have found it essential to take great care in constraining the fitting procedure by using a block-diagonalization procedure, which we describe in detail.

cond-mat.mtrl-sci↗

arXiv1998

Spectrum of Neutral Helium in Strong Magnetic Fields

We present extensive and accurate calculations for the excited state spectrum of spin-polarized neutral helium in a range of magnetic field strengths up to $10^{12}$ G. Of considerable interest to models of magnetic white dwarf stellar atmospheres, we also present results for the dipole strengths of the low lying transitions among these states. Our methods rely on a systematically saturated basis set approach to solving the Hartree--Fock self-consistent field equations, combined with an ``exact'' stochastic method to estimate the residual basis set truncation error and electron correlation effects. We also discuss the applicability of the adiabatic approximation to strongly magnetized multi-electron atoms.

physics.atom-ph↗