Computing
Parent: Computing Sciences
eScholarship stats: Breakdown by Item for December, 2024 through March, 2025
| Item | Title | Total requests | Download | View-only | %Dnld |
|---|---|---|---|---|---|
| 4sf7n3pc | Nuclear Physics Network Requirements Review: One-Year Update | 448 | 194 | 254 | 43.3% |
| 00j3z3rd | AMReX: a framework for block-structured adaptive mesh refinement | 363 | 345 | 18 | 95.0% |
| 4mj3d1jb | The MyESnet Portal: Making the Network Visible | 333 | 154 | 179 | 46.2% |
| 3nx4d18c | Author Correction: The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data | 120 | 37 | 83 | 30.8% |
| 9wp5j0dq | Nuclear Physics Exascale Requirements Review: An Office of Science review sponsored jointly by Advanced Scientific Computing Research and Nuclear Physics, June 15 - 17, 2016, Gaithersburg, Maryland | 85 | 68 | 17 | 80.0% |
| 6j5521rr | Editorial | 80 | 3 | 77 | 3.8% |
| 0t36p3hn | Lambda Architecture for Cost-Effective Batch and Speed Big Data Processing | 68 | 52 | 16 | 76.5% |
| 2xf0f1dj | The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data | 59 | 36 | 23 | 61.0% |
| 5z934420 | Advances in Cross-Cutting Ideas for Computational Climate Science | 57 | 16 | 41 | 28.1% |
| 3vf1w91z | Report of the DOE Workshop on Management, Analysis, and Visualization of Experimental and Observational data – The Convergence of Data and Computing | 55 | 27 | 28 | 49.1% |
| 7298g7m9 | A Guide to Using GitHub for Developing and Versioning Data Standards and Reporting Formats | 53 | 21 | 32 | 39.6% |
| 81v261jh | PageRank, HITS and a unified framework for link analysis | 53 | 26 | 27 | 49.1% |
| 8md8q9kq | An Architecture For Edge Networking Services | 52 | 0 | 52 | 0.0% |
| 02x259pf | Randomized Algorithms for Scientific Computing (RASC) | 51 | 36 | 15 | 70.6% |
| 3b80v6zt | International Neuroscience Initiatives Through the Lens of High-Performance Computing | 51 | 16 | 35 | 31.4% |
| 6vb1r6c3 | PeleC: An adaptive mesh refinement solver for compressible reacting flows | 49 | 11 | 38 | 22.4% |
| 57t3r88k | A Parallel lanczos Method for Symmetric Generalized Eigenvalue Problems | 46 | 16 | 30 | 34.8% |
| 61j6m742 | 2019 Computing Sciences Strategic Plan | 45 | 25 | 20 | 55.6% |
| 8pv153t1 | Adaptive dimension reduction for clustering high dimensional data | 45 | 17 | 28 | 37.8% |
| 5vr0h58m | A conservative, thermodynamically consistent numerical approach for low Mach number combustion. Part I: Single-level integration | 44 | 27 | 17 | 61.4% |
| 1qs17737 | The future low-temperature geochemical data-scape as envisioned by the U.S. geochemical community | 43 | 21 | 22 | 48.8% |
| 12r566sn | ExaSAT: An exascale co-design tool for performance modeling | 40 | 18 | 22 | 45.0% |
| 0047q4b2 | High-Performance Computational Intelligence and Forecasting Technologies | 39 | 8 | 31 | 20.5% |
| 7v13c2dq | Network Hardware Virtualization for Application Provisioning in Core Networks | 37 | 15 | 22 | 40.5% |
| 0x7138n5 | Unmatched: 50 Years of Supercomputing, A Personal Journey Accompanying the Evolution of a Powerful Tool | 36 | 22 | 14 | 61.1% |
| 2sr9m6gk | Parameter Analysis of the VPIN (Volume synchronized Probability of Informed Trading) Metric | 36 | 18 | 18 | 50.0% |
| 3t75f0qg | Performance characterization of scientific workflows for the optimal use of Burst Buffers | 36 | 11 | 25 | 30.6% |
| 1ds6v8ww | Challenging problems of quality assurance and quality control (QA/QC) of meteorological time series data | 34 | 6 | 28 | 17.6% |
| 28b779q1 | The TOP500 List and Progress in High-Performance Computing | 34 | 18 | 16 | 52.9% |
| 6gk8b245 | Thick-Restart Lanczos Method for Electronic Structure Calculations | 34 | 12 | 22 | 35.3% |
| 7876x5ks | Search for mixing-induced CP violation using partial reconstruction of B¯0→D*+Xℓ-ν¯ℓ and kaon tagging | 34 | 12 | 22 | 35.3% |
| 3q12x1gh | Perspectives for self-driving labs in synthetic biology | 33 | 21 | 12 | 63.6% |
| 7mv4p0m8 | A science data gateway for environmental management | 33 | 13 | 20 | 39.4% |
| 611154fz | Iterative Importance Sampling Algorithms for Parameter Estimation | 32 | 23 | 9 | 71.9% |
| 6km2b4fz | On the Equivalence of Nonnegative Matrix Factorization and K-means - Spectral Clustering | 32 | 8 | 24 | 25.0% |
| 8qb0p7j7 | Distributed Acoustic Sensing Using Dark Fiber for Near-Surface Characterization and Broadband Seismic Event Detection | 32 | 10 | 22 | 31.3% |
| 9tg9045c | Beyond 100 Gb/s: capacity, flexibility, and network optimization [Invited] | 32 | 22 | 10 | 68.8% |
| 35z8t8gn | The Early Years and Evolution of the DOE Computational Science Graduate Fellowship Program | 31 | 18 | 13 | 58.1% |
| 0ft5q1xv | NERSC "Visualization Greenbook" Future visualization needs of the DOE computational science community hosted at NERSC | 30 | 7 | 23 | 23.3% |
| 8pj0n2v2 | FABRIC: A National-Scale Programmable Experimental Network Infrastructure | 30 | 19 | 11 | 63.3% |
| 97d284ps | Machine learning-based Analysis of COVID-19 Pandemic Impact on US Research Networks | 30 | 17 | 13 | 56.7% |
| 7g6632bn | The NAS Parallel Benchmarks | 29 | 5 | 24 | 17.2% |
| 9wr5396s | A broad exploration of nonlinear dynamics in microbial systems motivated by chemostat experiments producing deterministic chaos. | 29 | 10 | 19 | 34.5% |
| 4xn2z9gq | Big-Data Science: Infrastructure Impact | 28 | 8 | 20 | 28.6% |
| 8kf319cb | A taxonomy of constraints in black-box simulation-based optimization | 28 | 18 | 10 | 64.3% |
| 8nb5w553 | Enabling FAIR data in Earth and environmental science with community-centric (meta)data reporting formats | 28 | 4 | 24 | 14.3% |
| 23r0f11d | Constructing a Simulation Surrogate with Partially Observed Output | 27 | 13 | 14 | 48.1% |
| 2db7v922 | Enabling intent to configure scientific networks for high performance demands | 27 | 8 | 19 | 29.6% |
| 2g71q95s | Connected OFCity Challenge: Addressing the Digital Divide in the Developing World | 27 | 13 | 14 | 48.1% |
| 3bd5p5j7 | Adaptive Projection Subspace Dimension for the Thick-Restart Lanczos Method | 26 | 7 | 19 | 26.9% |
Note: Due to the evolving nature of web traffic, the data presented here should be considered approximate and subject to revision. Learn more.