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The Performance-Portability Trade-Off Challenge in Next Generation Particle-In-Cell Simulations
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Characterizing the Pareto Optimal Trade-off between Model-Based Information Content and Measurements Cost
This is a poster for the May 31 - June 3, 2023, SIAM conference with the goal to present advances in mathematical modeling and a case study as part of the Carbon Capture Simulation Initiative.
DenKv: Addressing Design Trade-offs of Key-value Stores for Scientific Applications
High-performance computing (HPC) facilities have employed flash-based storage tier near to compute nodes to absorb high I/O demand by HPC applications during periodic system-level checkpoints. To accelerate these checkpoints, proxy-based distributed key-value stores (PD-KVS) gained particular attention for their flexibility to support multiple backends and different network configurations. PD-KVS rely internally on monolithic KVS, such as LevelDB or RocksDB, to exploit the KV interface and query support. However, PD-KVS are unaware of the high redundancy factor in checkpoint data, which can be up to GBs to TBs, and therefore, tend to generate high write and space amplification on these storage layers. In this paper, we propose DenKv which is deduplication-extended node-local LSM-tree-based KVS. DenKv employs asynchronous partially inline dedup (APID) and aims to maintain the performance characteristics of LSM-tree-based KVS while reducing the write and space amplification problems. We implemented DenKv atop BlobDB and showed that our proposed solution maintains performance while reducing write amplification up to 2× and space amplification by 4× on average.
RF Performance and TID Hardness Trade-offs in Annular 45-nm RF SOI CMOS Devices.
Abstract not provided.
Transmutation, Burn-Up and Fuel Fabrication Trade-Offs in Reduced-Moderation Water Reactor Thorium Fuel Cycles - 13502
Multiple recycle of long-lived actinides has the potential to greatly reduce the required storage time for spent nuclear fuel or high level nuclear waste. This is generally thought to require fast reactors as most transuranic (TRU) isotopes have low fission probabilities in thermal reactors. Reduced-moderation LWRs are a potential alternative to fast reactors with reduced time to deployment as they are based on commercially mature LWR technology. Thorium (Th) fuel is neutronically advantageous for TRU multiple recycle in LWRs due to a large improvement in the void coefficient. If Th fuel is used in reduced-moderation LWRs, it appears neutronically feasible to achieve full actinide recycle while burning an external supply of TRU, with related potential improvements in waste management and fuel utilization. In this paper, the fuel cycle of TRU-bearing Th fuel is analysed for reduced-moderation PWRs and BWRs (RMPWRs and RBWRs). RMPWRs have the advantage of relatively rapid implementation and intrinsically low conversion ratios. However, it is challenging to simultaneously satisfy operational and fuel cycle constraints. An RBWR may potentially take longer to implement than an RMPWR due to more extensive changes from current BWR technology. However, the harder neutron spectrum can lead to favourable fuel cycle performance. A two-stage fuel cycle, where the first pass is Th-Pu MOX, is a technically reasonable implementation of either concept. The first stage of the fuel cycle can therefore be implemented at relatively low cost as a Pu disposal option, with a further policy option of full recycle in the medium term. (authors)
Measure This, Not That: Pareto Optimal Trade-Offs between Model-Based Information Content and Measurements Cost
The slides present a novel convex optimization formulation to compute the best set of measurements for multi-response dynamical systems with asynchronous time steps that maximize the Fisher information content subject to budget constraints. The trace (A-optimality) or determinant (D-optimality) of the Fisher Information Matrix (FIM) quantifies the information content. The framework supports arbitrary (positive semi-definite) variance and covariances between every pair of responses and their time steps.
A Framework for Assessing Economic and Environmental Trade-offs of Internalized Emission Costs in ERCOT Grid Planning
The power grid is on the cusp of a massive transition driven by three major areas: 1) the growth in demand for electricity, 2) efforts to decarbonize the United States economy, and 3) a desire to mitigate social disparities from the impact of electricity generation on local populations. However, most studies of the electricity sector do not include equity impacts in their models. This study seeks to do so by developing a comprehensive and generalizable model tailored to the Electric Reliability Council of Texas (ERCOT) grid, designed to incorporate the equity impacts of electricity generation in a decarbonized and resilient framework. To integrate equity into our research, we incorporate environmental externalities into our capacity expansion model of ERCOT. Specifically, we factor in intermediate-level local marginal damages of precursor pollutants (NH3, NOx, primary PM2.5, SO2, and VOC) and global pollutant CO2 into the cost of generating electricity. We do this by taking into account county population, county ambient pollution concentration, and generator emission rates. Leveraging open-source modeling tools, such as PowerGenome, pyGRETA, and GenX we construct a county-level model to account for these costs. We integrate these marginal damages into the variable operations and maintenance costs of generators, for both existing and potential future builds. This study’s findings suggest that the value of a dynamic social cost of carbon (SSC) will cover criteria pollutant marginal damages within the ERCOT grid and solar and wind is expected to increase out to 2035. Key metrics evaluated within this research include fuel mix distribution across technologies, transmission and grid infrastructure costs, CO2 emissions, local pollutants marginal damages, and the variation in generation capacity built by the model. These results and framework can be used to support grid decisions that explicitly include distributional and procedural equity within a decarbonized and sustainable grid framework.
Ko’olauloa Community Resilience Hub Design Trade-off Study
Paper showing microgrid and energy efficiency tradeoffs for a case study for the Ko'olauloa Community resilience hub using HOMER and MDT.
Two-Tower Quantum Matrix Chain Multiplication: Trading Qubits for Depth
Matrix chain multiplication -- computing $\mathcal{W} = M^{(0)}\cdots M^{(K-1)}$ where $M^{(k)} \in \mathbb{R}^{P_k \times P_{k+1}}$-- arises in scientific computing, machine learning, and graph analysis. Despite the importance of this problem, for chains of distinct matrices, the classical number of operations grows linearly with the chain length $K$ and polynomially in the matrix dimensions. We present \emph{Two-Tower Matrix Multiplication}, a quantum subroutine that encodes the product $\mathcal{W}$ of the $K$ matrices into a quantum state in circuit depth $\mathcal{O}(\max_{k} \mathrm{polylog} (P_k P_{k+1}))$, which is independent of~$K$ within the QRAM-based state-preparation model, whereas the qubit count is $\mathcal{O}\bigl(\sum_{k} \log P_k \bigr)$; the total gate count remains linear in $K$, so the gain is in the circuit depth. The construction interleaves state-preparation operators across two layers; within each layer, all operators act on disjoint registers and execute in parallel. This subroutine can be specialized for the chain-vector case, which computes the product of $K-1$ matrices applied to a vector. We prove the correctness of the subroutine for all $K$ and provide two implementations using the Qiskit and QCLAB frameworks. The subroutine is applicable to any downstream quantum algorithm that operates on a matrix encoded in the statevector, including norm estimation, graph-matrix powers, linear system solving, and quantum machine learning kernels.
Characterization of adaptive statistical iterative reconstruction algorithm for dose reduction in CT: A pediatric oncology perspective
Purpose: This study demonstrates a means of implementing an adaptive statistical iterative reconstruction (ASiR Trade-Mark-Sign ) technique for dose reduction in computed tomography (CT) while maintaining similar noise levels in the reconstructed image. The effects of image quality and noise texture were assessed at all implementation levels of ASiR Trade-Mark-Sign . Empirically derived dose reduction limits were established for ASiR Trade-Mark-Sign for imaging of the trunk for a pediatric oncology population ranging from 1 yr old through adolescence/adulthood. Methods: Image quality was assessed using metrics established by the American College of Radiology (ACR) CT accreditation program. Each image quality metric was tested using the ACR CT phantom with 0%-100% ASiR Trade-Mark-Sign blended with filtered back projection (FBP) reconstructed images. Additionally, the noise power spectrum (NPS) was calculated for three common reconstruction filters of the trunk. The empirically derived limitations on ASiR Trade-Mark-Sign implementation for dose reduction were assessed using (1, 5, 10) yr old and adolescent/adult anthropomorphic phantoms. To assess dose reduction limits, the phantoms were scanned in increments of increased noise index (decrementing mA using automatic tube current modulation) balanced with ASiR Trade-Mark-Sign reconstruction to maintain noise equivalence of the 0% ASiR Trade-Mark-Sign image. Results: The ASiR Trade-Mark-Sign algorithm did not produce any unfavorable effects on image quality as assessed by ACR criteria. Conversely, low-contrast resolution was found to improve due to the reduction of noise in the reconstructed images. NPS calculations demonstrated that images with lower frequency noise had lower noise variance and coarser graininess at progressively higher percentages of ASiR Trade-Mark-Sign reconstruction; and in spite of the similar magnitudes of noise, the image reconstructed with 50% or more ASiR Trade-Mark-Sign presented a more smoothed appearance than the pre-ASiR Trade-Mark-Sign 100% FBP image. Finally, relative to non-ASiR Trade-Mark-Sign images with 100% of standard dose across the pediatric phantom age spectrum, similar noise levels were obtained in the images at a dose reduction of 48% with 40% ASIR Trade-Mark-Sign and a dose reduction of 82% with 100% ASIR Trade-Mark-Sign . Conclusions: The authors' work was conducted to identify the dose reduction limits of ASiR Trade-Mark-Sign for a pediatric oncology population using automatic tube current modulation. Improvements in noise levels from ASiR Trade-Mark-Sign reconstruction were adapted to provide lower radiation exposure (i.e., lower mA) instead of improved image quality. We have demonstrated for the image quality standards required at our institution, a maximum dose reduction of 82% can be achieved using 100% ASiR Trade-Mark-Sign ; however, to negate changes in the appearance of reconstructed images using ASiR Trade-Mark-Sign with a medium to low frequency noise preserving reconstruction filter (i.e., standard), 40% ASiR Trade-Mark-Sign was implemented in our clinic for 42%-48% dose reduction at all pediatric ages without a visually perceptible change in image quality or image noise.
PORTNUS Project
The objective of the Portunus Project is to create large, automated offshore ports that will the pace and scale of international trade. Additionally, these ports would increase the number of U.S. domestic trade vessels needed, as the imported goods would need to be transported from these offshore platforms to land-based ports such as Boston, Los Angeles, and Newark. Currently, domestic trade in the United States can only be conducted by vessels that abide by the Merchant Marine Act of 1920 – also referred to as the Jones Act. The Jones Act stipulates that vessels involved in domestic trade must be U.S. owned, U.S. built, and manned by a crew made up of U.S. citizens. The Portunus Project would increase the number of Jones Act vessels needed, which raises an interesting economic concern. Are Jones Act ships more expensive to operate than foreign vessels? Would it be more economically efficient to modify the Jones Act and allow vessels manned by foreign crews to engage in U.S. domestic trade? While opposition to altering the Jones Act is strong, it is important to consider the possibility that ship-owners who employ foreign crews will lobby for the chance to enter a growing domestic trade market. Their success would mean potential job loss for thousands of Americans currently employed in maritime trade.
Assessing the Evolving Fragility of the Global Food System
The world food crisis in 2008 highlighted the susceptibility of the global food system to price shocks. Here we use annual staple food production and trade data from 1992-2009 to analyse the changing properties of the global food system. Over the 18-year study period, we show that the global food system is relatively homogeneous (85 of countries have low or marginal food self-sufficiency) and increases in complexity, with the number of global wheat and rice trade connections doubling and trade flows increasing by 42 and 90, respectively. The increased connectivity and flows within these global trade networks suggest that the global food system is vulnerable to systemic disruptions, especially considering the tendency for exporting countries to switch to non-exporting states during times of food scarcity in the global markets. To test this hypothesis, we superimpose continental-scale disruptions on the wheat and rice trade networks. We find greater absolute reductions in global wheat and rice exports along with larger losses in network connectivity as the networks evolve due to disruptions in European wheat and Asian rice production. Importantly, our findings indicate that least developed countries suffer greater import losses in more connected networks through their increased dependence on imports for staple foods (due to these large-scale disturbances): mean (median) wheat losses as percentages of staple food supply are 8.9 (3.8) for 1992-1996, increasing to 11 (5.7) for 20052009. Over the same intervals, rice losses increase from 8.2 (2.2) to 14 (5.2). Our work indicates that policy efforts should focus on balancing the efficiency of international trade (and its associated specialization) with increased resilience of domestic production and global demand diversity.
The Establishment of a Formal Midwest Renewable Energy Tracking System (M-RETS) Organization
The objectives identified in requesting and utilizing this funding has been met. The goal was to establish a formal, multi-jurisdictional organization to: (1) ensure the policy objectives of the participating jurisdictions are addressed through increased tradability of the Renewable Energy Credits (RECs) from M-RETS and to eliminate the possibility that a single jurisdiction will be the sole arbiter of the operation of the system; (2) facilitate the establishment of REC standards including the attributes related to, the creation, trading, and interaction with other trading and tracking systems; and (3) have a centralized and established organization that will be responsible for the contracting and governance responsibilities of a multi-jurisdictional tracking system. The M-RETS Inc. Board ensures that the system remains policy neutral; that the attributes of generation are tracked in a way that allows the system users to easily identify and trade relevant RECs; that the system can add jurisdictions as needed or desired; and that the tracking system operate in such a way to allow for the greatest access possible for those participating in other tracking or trading systems by allowing those systems to negotiate with a single M-RETS entity for the import and export of RECs. M-RETS as an organizational body participates and often leads the discussions related to the standardization of RECs and increasing the tradability of M-RETS RECs. M-RETS is a founding member of the Environmental Trading Network of North America (ETNNA) and continues to take a leadership role in the development of processes to facilitate trading among tracking systems and to standardize REC definitions. The Board of Directors of M-RETS, Inc., the non-profit corporation, continues to hold telephone/internet Board meetings. Legal counsel continues working with the board and APX management on a new agreement with APX. The board expects to have an agreement and corresponding fee structure in place by January 2011. The Board has recently approved exports to three other tracking systems and is in discussions about imports to the system. Below are the tasks outlined in the request and attached you will find the relevant documentation.
A Big Data Approach to Analyzing Market Volatility
Understanding the microstructure of the financial market requires the processing of a vast amount of data related to individual trades, and sometimes even multiple levels of quotes. Analyzing such a large volume of data requires tremendous computing power that is not easily available to financial academics and regulators. Fortunately, public funded High Performance Computing (HPC) power is widely available at the National Laboratories in the US. In this paper we demonstrate that the HPC resource and the techniques for data-intensive sciences can be used to greatly accelerate the computation of an early warning indicator called Volume-synchronized Probability of Informed trading (VPIN). The test data used in this study contains five and a half year's worth of trading data for about 100 most liquid futures contracts, includes about 3 billion trades, and takes 140GB as text files. By using (1) a more efficient file format for storing the trading records, (2) more effective data structures and algorithms, and (3) parallelizing the computations, we are able to explore 16,000 different ways of computing VPIN in less than 20 hours on a 32-core IBM DataPlex machine. Our test demonstrates that a modest computer is sufficient to monitor a vast number of trading activities in real-time – an ability that could be valuable to regulators. Our test results also confirm that VPIN is a strong predictor of liquidity-induced volatility. With appropriate parameter choices, the false positive rates are about 7% averaged over all the futures contracts in the test data set. More specifically, when VPIN values rise above a threshold (CDF > 0.99), the volatility in the subsequent time windows is higher than the average in 93% of the cases.
Greenhouse Gas Mitigation Options in ISEEM Global Energy Model: 2010-2050 Scenario Analysis for Least-Cost Carbon Reduction in Iron and Steel Sector
The goal of the modeling work carried out in this project was to quantify long-term scenarios for the future emission reduction potentials in the iron and steel sector. The main focus of the project is to examine the impacts of carbon reduction options in the U.S. iron and steel sector under a set of selected scenarios. In order to advance the understanding of carbon emission reduction potential on the national and global scales, and to evaluate the regional impacts of potential U.S. mitigation strategies (e.g., commodity and carbon trading), we also included and examined the carbon reduction scenarios in China’s and India’s iron and steel sectors in this project. For this purpose, a new bottom-up energy modeling framework, the Industrial Sector Energy Efficiency Modeling (ISEEM), (Karali et al. 2012) was used to provide detailed annual projections starting from 2010 through 2050. We used the ISEEM modeling framework to carry out detailed analysis, on a country-by-country basis, for the U.S., China’s, and India’s iron and steel sectors. The ISEEM model applicable to iron and steel section, called ISEEM-IS, is developed to estimate and evaluate carbon emissions scenarios under several alternative mitigation options - including policies (e.g., carbon caps), commodity trading, and carbon trading. The projections will help us to better understand emission reduction potentials with technological and economic implications. The database for input of ISEEM-IS model consists of data and information compiled from various resources such as World Steel Association (WSA), the U.S. Geological Survey (USGS), China Steel Year Books, India Bureau of Mines (IBM), Energy Information Administration (EIA), and recent LBNL studies on bottom-up techno-economic analysis of energy efficiency measures in the iron and steel sector of the U.S., China, and India, including long-term steel production in China. In the ISEEM-IS model, production technology and manufacturing details are represented, in addition to the extensive data compiled from recent studies on bottom-up representation of efficiency measures for the sector. We also defined various mitigation scenarios including long-term production trends to project country-specific production, energy use, trading, carbon emissions, and costs of mitigation. Such analyses can provide useful information to assist policy-makers when considering and shaping future emissions mitigation strategies and policies. The technical objective is to analyze the costs of production and CO 2 emission reduction in the U.S, China, and India’s iron and steel sectors under different emission reduction scenarios, using the ISEEM-IS as a cost optimization model. The scenarios included in this project correspond to various CO 2 emission reduction targets for the iron and steel sector under different strategies such as simple CO 2 emission caps (e.g., specific reduction goals), emission reduction via commodity trading, and emission reduction via carbon trading.