Pete Beckman
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View article: XaaS: Acceleration as a Service to Enable Productive High-Performance Cloud Computing
XaaS: Acceleration as a Service to Enable Productive High-Performance Cloud Computing Open
High-performance computing (HPC) and the cloud have evolved independently, specializing their innovations into performance or productivity. Acceleration as a Service (XaaS) is a recipe to empower both fields with a shared execution platfor…
View article: XaaS: Acceleration as a Service to Enable Productive High-Performance Cloud Computing
XaaS: Acceleration as a Service to Enable Productive High-Performance Cloud Computing Open
HPC and Cloud have evolved independently, specializing their innovations into performance or productivity. Acceleration as a Service (XaaS) is a recipe to empower both fields with a shared execution platform that provides transparent acces…
View article: CROCUS Air Quality Data at Chicago State University Prairie Site
CROCUS Air Quality Data at Chicago State University Prairie Site Open
The Air Quality Transmitter (AQT) (Vaisala AQT530) instrument provides observations on meteorological conditions, including particulate matter (PM2.5, PM10), gas species concentrations (Nitric Oxide (NO), Nitrogen Dioxide (NO2), Ozone (O3)…
View article: CROCUS Weather Data at University of Illinois - Chicago Tower
CROCUS Weather Data at University of Illinois - Chicago Tower Open
Vaisala WXT sensor is an all-in-one weather instrument that provides 6 of the most important weather parameters: barometric pressure, temperature, relative humidity, rainfall, wind speed and direction. Temperature, pressure, relative humid…
View article: CROCUS Air Quality Data at Argonne National Laboratory Prairie Site
CROCUS Air Quality Data at Argonne National Laboratory Prairie Site Open
The AQT (Vaisala AQT530) instrument provides observations on meteorological conditions, including particulate matter (PM2.5, PM10), gas species concentrations (NO, NO2, O3, CO), and environment temperature and moisture. These measurements …
View article: CROCUS Air Quality Data at Northeastern Illinois University Rooftop
CROCUS Air Quality Data at Northeastern Illinois University Rooftop Open
This dataset is from the Department of Energy Office of Science funded project, Community Research on Urban and Climate Science (CROCUS) (https://crocus-urban.org/). The AQT (Vaisala AQT530) instrument provides observations on meteorologic…
View article: CROCUS Weather Data at Chicago State University Prairie Site
CROCUS Weather Data at Chicago State University Prairie Site Open
Vaisala WXT sensor is an all-in-one weather instrument that provides 6 of the most important weather parameters: barometric pressure, temperature, relative humidity, rainfall, wind speed and direction. Temperature, pressure, relative humid…
View article: CROCUS Weather Data at Argonne National Laboratory Prairie Site
CROCUS Weather Data at Argonne National Laboratory Prairie Site Open
Vaisala WXT sensor is an all-in-one weather instrument that provides 6 of the most important weather parameters: barometric pressure, temperature, relative humidity, rainfall, wind speed and direction. Temperature, pressure, relative humid…
View article: CROCUS Air Quality Data at University of Illinois - Chicago Tower
CROCUS Air Quality Data at University of Illinois - Chicago Tower Open
The AQT (Vaisala AQT530) instrument provides observations on meteorological conditions, including particulate matter (PM2.5, PM10), gas species concentrations (NO, NO2, O3, CO), and environment temperature and moisture. These measurements …
View article: Benchmarking and In-depth Performance Study of Large Language Models on Habana Gaudi Processors
Benchmarking and In-depth Performance Study of Large Language Models on Habana Gaudi Processors Open
Transformer models have achieved remarkable success in various machine learning tasks but suffer from high computational complexity and resource requirements. The quadratic complexity of the self-attention mechanism further exacerbates the…
View article: Networked Sensing for Radiation Detection, Localization, and Tracking
Networked Sensing for Radiation Detection, Localization, and Tracking Open
The detection, identification, and localization of illicit radiological and nuclear material continue to be key components of nuclear non-proliferation and nuclear security efforts around the world. Networks of radiation detectors deployed…
View article: Adversarial Predictions of Data Distributions Across Federated Internet-of-Things Devices
Adversarial Predictions of Data Distributions Across Federated Internet-of-Things Devices Open
Federated learning (FL) is increasingly becoming the default approach for training machine learning models across decentralized Internet-of-Things (IoT) devices. A key advantage of FL is that no raw data are communicated across the network…
View article: Networked Sensing for Radiation Detection, Localization, and Tracking
Networked Sensing for Radiation Detection, Localization, and Tracking Open
The detection, identification, and localization of illicit radiological and nuclear material continue to be key components of nuclear non-proliferation and nuclear security efforts around the world. Networks of radiation detectors deployed…
View article: ARMing the Edge: Designing Edge Computing–Capable Machine Learning Algorithms to Target ARM Doppler Lidar Processing
ARMing the Edge: Designing Edge Computing–Capable Machine Learning Algorithms to Target ARM Doppler Lidar Processing Open
There is a need for long-term observations of cloud and precipitation fall speeds in validating and improving rainfall forecasts from climate models. To this end, the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user f…
View article: Advanced Research Directions on AI for Science, Energy, and Security: Report on Summer 2022 Workshops
Advanced Research Directions on AI for Science, Energy, and Security: Report on Summer 2022 Workshops Open
This is a report about a series of workshops sponsored by the Department of Energy (DOE) to gather input on new and rapidly emerging opportunities and challenges of scientific AI. The members of the workshops believes that AI can have a fo…
View article: Optimizing cloud motion estimation on the edge with phase correlation and optical flow
Optimizing cloud motion estimation on the edge with phase correlation and optical flow Open
Phase correlation (PC) is a well-known method for estimating cloud motion vectors (CMVs) from infrared and visible spectrum images. Commonly, phase shift is computed in the small blocks of the images using the fast Fourier transform. In th…
View article: Let’s Unleash the Network Judgment: A Self-Supervised Approach for Cloud Image Analysis
Let’s Unleash the Network Judgment: A Self-Supervised Approach for Cloud Image Analysis Open
Accurate cloud type identification and coverage analysis are crucial in understanding the Earth’s radiative budget. Traditional computer vision methods rely on low-level visual features of clouds for estimating cloud coverage or sky condit…
View article: Doppler spectra from ARM Doppler Lidar during ARMing the Edge
Doppler spectra from ARM Doppler Lidar during ARMing the Edge Open
There is a need for long-term observations of cloud and precipitation fall speeds in validating and improving rainfall forecasts from climate models. To this end, the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user f…
View article: SOLAR: A Highly Optimized Data Loading Framework for Distributed Training of CNN-based Scientific Surrogates
SOLAR: A Highly Optimized Data Loading Framework for Distributed Training of CNN-based Scientific Surrogates Open
CNN-based surrogates have become prevalent in scientific applications to replace conventional time-consuming physical approaches. Although these surrogates can yield satisfactory results with significantly lower computation costs over smal…
View article: Comment on amt-2022-159
Comment on amt-2022-159 Open
Abstract. Phase correlation (PC) is a well-known method for estimating cloud motion vectors (CMVs) from infrared and visible spectrum images. Commonly, phase shift is computed in the small blocks of the images using the fast Fourier transf…
View article: Phase correlation on the edge for estimating cloud motion
Phase correlation on the edge for estimating cloud motion Open
Phase Correlation (PC) is a well-known method for estimating cloud motion vectors (CMV) from infrared and visible spectrum images. Commonly phase-shift is computed in the small blocks of the images using the fast Fourier transform. In this…
View article: Hands-On Computer Science: The Array of Things Experimental Urban Instrument
Hands-On Computer Science: The Array of Things Experimental Urban Instrument Open
Chicago's Array of Things (AoT) project is aptly described as a technology experiment or a "smart city" prototype. The concept of such an extensible "instrument" arose within a larger translational research vision applying computer science…
View article: Prediction of Solar Irradiance and Photovoltaic Solar Energy Product Based on Cloud Coverage Estimation Using Machine Learning Methods
Prediction of Solar Irradiance and Photovoltaic Solar Energy Product Based on Cloud Coverage Estimation Using Machine Learning Methods Open
Cloud cover estimation from images taken by sky-facing cameras can be an important input for analyzing current weather conditions and estimating photovoltaic power generation. The constant change in position, shape, and density of clouds, …
View article: NUMA-AWARE DATA MANAGEMENT FOR NEUTRON CROSS SECTION DATA IN CONTINUOUS ENERGY MONTE CARLO NEUTRON TRANSPORT SIMULATION
NUMA-AWARE DATA MANAGEMENT FOR NEUTRON CROSS SECTION DATA IN CONTINUOUS ENERGY MONTE CARLO NEUTRON TRANSPORT SIMULATION Open
The calculation of macroscopic neutron cross-sections is a fundamental part of the continuous-energy Monte Carlo (MC) neutron transport algorithm. MC simulations of full nuclear reactor cores are computationally expensive, making high-accu…
View article: Measuring Cities with Software-Defined Sensors
Measuring Cities with Software-Defined Sensors Open
The Chicago Array of Things (AoT) project, funded by the US National Science Foundation, created an experimental, urban-scale measurement capability to support diverse scientific studies. Initially conceived as a traditional sensor network…