Evan Harvey

dblp:276/5734 · DBLP profile ↗
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3ranked-venue papers
1as first author
3since 2021 · last 2024
0000-0003-2772-8053ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Software engineering, systems software and programming languages · 2 · 1 first-author · 2 since 2021Systems, architecture and hardware · 1 · 1 since 2021Applied, interdisciplinary, general and emerging computing · 1 · 1 first-author · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
Parallel and multicore computing · 75% High-performance computing · 25%
Interdisciplinary, comprehensive, and emerging computing
1 paper
Computational science and engineering · 100%
Software engineering, system software, and programming languages
1 paper
Software maintenance and evolution · 100%

Topics — the 6 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Computational science and engineering
scientific workflow
0.812024
Towards Long-Term Scientific Model Sustainment at Sandia National Laboratories · ASE 2024
Software maintenance and evolution
software sustainability
0.812024
Towards Long-Term Scientific Model Sustainment at Sandia National Laboratories · ASE 2024
Parallel and multicore computing › parallel programming models › structured parallelism
hierarchical parallelism
0.612022
Kokkos 3: Programming Model Extensions for the Exascale Era · IEEE Trans. Parallel Distributed Syst. 2022
Parallel and multicore computing
parallel programming models
0.612022
Kokkos 3: Programming Model Extensions for the Exascale Era · IEEE Trans. Parallel Distributed Syst. 2022
High-performance computing › performance engineering
performance portability
0.612022
Kokkos 3: Programming Model Extensions for the Exascale Era · IEEE Trans. Parallel Distributed Syst. 2022
Parallel and multicore computing › parallel programming models
portable programming models
0.612022
Kokkos 3: Programming Model Extensions for the Exascale Era · IEEE Trans. Parallel Distributed Syst. 2022

Methods — techniques the papers use, named apart from their topics

workflow management · 1.5benchmarking · 0.6
YearPublicationVenuePosition
2024 Towards Long-Term Scientific Model Sustainment at Sandia National Laboratories
abstract
Scientific modeling and simulation software is ubiquitous at Sandia National Laboratories and is integral to providing empirical justification to critical mission decisions. Models are increasingly being expressed as workflows to simplify the many steps needed in scientific analyses but keeping these models and workflows alive for the decades-long timescales needed by Sandia remains a struggle. Additionally, the manual use and (lack of) maintenance of these models creates significant risks for duplicated work and model capability loss over time from changing personnel and computing environments. To address these issues, we are building the Engineering Common Modeling Framework (ECMF), a platform for scientific model sustainment at Sandia. ECMF enables the automatic evaluation of models over time and will ensure that models created at Sandia are discoverable and ready to be revisited, extended, and reused. In this paper, we report our current and planned capabilities as well as lessons learned from our framework development process.
Christian Gilbertson, Reed Milewicz, Eric Berquist, Aaron Brundage, John Engelmann, Brian Evans, Nicholas Francis, Ernest Friedman-Hill, Samuel Grayson, Evan Harvey, Eric Ho, Edward Hoffman, Kevin Irick, Anagha Krishna, Aaron Moreno, Joshua B. Teves
ASE10
2022 Half-Precision Scalar Support in Kokkos and Kokkos Kernels: An Engineering Study and Experience Report
abstract
To keep pace with the demand for innovation through scientific computing, modern scientific software development is increasingly reliant upon a rich and diverse ecosystem of software libraries and toolchains. Research software engineers (RSEs) responsible for that infrastructure perform highly integrative work, acting as a bridge between the hardware, the needs of researchers, and the software layers situated between them; relatively little, however, has been written about the role played by RSEs in that work and what support they need to thrive. To that end, we present a two-part report on the development of half-precision floating point support in the Kokkos Ecosystem. Half-precision computation is a promising strategy for increasing performance in numerical computing and is particularly attractive for emerging application areas (e.g., machine learning), but developing practicable, portable, and user-friendly abstractions is a nontrivial task. In the first half of the paper, we conduct an engineering study on the technical implementation of the Kokkos half-precision scalar feature and showcase experimental results; in the second half, we offer an experience report on the challenges and lessons learned during feature development by the first author. We hope our study provides a holistic view on scientific library development and surfaces opportunities for future studies into effective strategies for RSEs engaged in such work.
Evan Harvey, Reed Milewicz, Christian Trott, Luc Berger-Vergiat, Sivasankaran Rajamanickam
e-Science1
2022 Kokkos 3: Programming Model Extensions for the Exascale Era
abstract
As the push towards exascale hardware has increased the diversity of system architectures, performance portability has become a critical aspect for scientific software. We describe the Kokkos Performance Portable Programming Model that allows developers to write single source applications for diverse high-performance computing architectures. Kokkos provides key abstractions for both the compute and memory hierarchy of modern hardware. We describe the novel abstractions that have been added to Kokkos version 3 such as hierarchical parallelism, containers, task graphs, and arbitrary-sized atomic operations to prepare for exascale era architectures. We demonstrate the performance of these new features with reproducible benchmarks on CPUs and GPUs.
Christian Trott, Damien Lebrun-Grandié, Daniel Arndt 0003, Jan Ciesko, Vinh Q. Dang, Nathan D. Ellingwood, Rahulkumar Gayatri, Evan Harvey, Daisy S. Hollman, Daniel Ibanez, Nevin Liber, Jonathan R. Madsen, Jeff Miles, David Poliakoff, Amy Powell, Sivasankaran Rajamanickam, Mikael Simberg, Daniel Sunderland, Bruno Turcksin, Jeremiah J. Wilke
IEEE Trans. Parallel Distributed Syst.8