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DOE OSTI2023

Software-Hardware Co-design of Heterogeneous SmartNIC System for Recommendation Models Inference and Training

Deep Learning Recommendation Models (DLRMs) are critical applications in various domains and have evolved as one of the single largest machine learning applications. Trillions of DLRM parameters exceed the on-chip memory capacity of GPUs. Large-scale multi-node systems are required for distributed DLRM inference and training, which suffer from the all-to-all communication bottleneck, mainly limiting the scalability of ever-growing DLRMs. In recent years, SmartNICs have evolved with coupled computation and communication capabilities providing opportunities for a powerful heterogeneous device in the system. However, there isn't such a distributed system that fully leverages the abundant smartNIC resources that resolve the scalability issue of DLRMs. In this work, we proposed a software-hardware co-design of a heterogeneous smartNIC system that resolves the communication bottleneck of distributed DLRMs, mitigates the memory bandwidth pressure, and improves computation efficiency. We provide a set of smartNIC designs of cache systems (including local cache and remote cache) and smartNIC computation kernels which reduce data movement, relieve memory lookup intensity, and improve the GPU's computation efficiency. In addition, we propose a graph algorithm that improves the data locality of queries within batches which optimizes the overall system performance with higher data reuse. Our evaluation shows that our system achieves 2.1x latency speedup for inference and 1.6x throughput speedup for training.

Guo, Anqi↗

DOE OSTI2021

Paying it Forward: How an Emerging Unconventional Play can Hit the Ground Running

While every tight oil play is unique, there are lessons that can be transferred from one play to another to improve the efficiency and pace of production operations and development. These improvements may not fit precisely in every basin or play but generally hold to themes that can be tested against and built upon. Themes such as the quantity of proppant, longer lateral length, or the number of stages can be directly tied to increased productivity. However, there are diminishing returns on these investment activities for which each operator, within a given play, will be required to identify and mitigate against. This is especially true as the industry steps in and begins developing new tight oil plays. In their nascent stages, these plays may have limited well penetrations and, as a result, limited geological and performance data from which to extrapolate. Pulling together an understanding of where the industry currently resides in terms of how to exploit these resources can provide a boost in terms of working towards greatly improved well completions. In 2019, the US EIA estimated that nearly 8 million barrels of oil per day were produced from tight oil reservoirs in the United States (US EIA, 2020). This represents over 60% of the domestic crude production, originating from multiple reservoirs in the Permian Basin (TX) as well as the Bakken (MT, ND), Eagle Ford (TX), Niobrara (CO, WY), and Anadarko Basin (OK) formations, among others. As such, there are 1,000s of wells across these numerous tight oil plays that can relate an informative story. To build this story, the interplay of geology, well spacing, lateral length, and stimulation, all critical to economic success, will be explored. This paper proposes to look back at these mature tight oil (and gas) basins and bring forth an understanding of what lessons can be applied to the emerging Powder River Basin tight oil reservoirs (Mowry and the Turner/Frontier). The authors will delve into the four broad topics of geology, well spacing, lateral length, and stimulation, highlighting case studies to demonstrate those lessons from established tight oil plays that will underpin planned activities at a Field Laboratory Test Site in the southern Powder River Basin.

02 PETROLEUM↗

DOE OSTI2023

Progressive evolutions of non-fused ring electron acceptors toward efficient organic solar cells with improved photocurrent and reduced energy loss

Resolving competitive counterbalance between high external quantum efficiency (EQE) response and low energy loss is critical for achieving efficient organic solar cells (OSCs), including those based on low-cost non-fused-ring electron acceptor (NFREA). In this work, we performed a comparable study by utilizing four NFREAs with progressive evolutions in molecular structures, energetic levels, spectral coverages, crystallinity, etc, to pair with polymer donor J52. By regulating the terminal and side chains of NFREAs, the enhanced intramolecular charge transfer (ICT) effect allows O-PC-EH possessing the broader spectral coverage for higher photocurrent, the reduced energetic offset enables O-PC-EH-based device owning higher luminescence property for lower energy loss, the strengthened crystallinity endows O-PC-EH-based blend better charge transport property for less charge recombination. With those comprehensive managements from molecule to blend properties, the J52:O-PC-EH-based OSCs achieved the best efficiency of 14.4% (certified: 14.1%) with benefits in all the three device parameters. Here, this work reveals the importance of fine-tuning molecular structures of NFREAs according to paired polymer donor for maximizing the device performances.

14 SOLAR ENERGY↗

DOE OSTI2022

Paintable Heat-Reflective Coatings for Low-Cost Energy Efficient Windows

The major objective of this effort is to manufacture a paintable coating to inexpensively retrofit energy-inefficient windows with a heat-reflective, visibly transparent film. This coating will drastically reduce cooling costs for millions of homes and buildings and lower the Nation’s greenhouse gas emissions. Widespread implementation could reduce the national consumption of electricity for cooling by billions of kWh, saving billions of dollars per year. This improved energy efficiency would decrease CO2 emissions by billions kg per year, the equivalent to removing millions of cars from the road. Although near-IR reflective adhesive films are commercially available products and have demonstrated significant energy efficiency enhancement, high upfront costs largely deter potential consumers across all sectors. The technology developed under this award was proposed to disrupt the building envelope market, by providing an inexpensive coating that can be directly applied by consumers to improve the energy efficiency of virtually all window types. The proof of concept for a paintable, DIY applicable, visibly transparent, and infrared reflective coating was achieved, laying the foundation for future technology development in this area.

14 SOLAR ENERGY↗

DOE OSTI2020

FLEET: Flexible Efficient Ensemble Training for Heterogeneous Deep Neural Networks

Parallel training of an ensemble of Deep Neural Networks (DNN) on a cluster of nodes is an effective approach to shorten the process of neural network architecture search and hyper-parameter tuning for a given learning task. Prior efforts have shown that data sharing, where the common preprocessing operation is shared across the DNN training pipelines, saves computational resources and improves pipeline efficiency. Data sharing strategy, however, performs poorly for a heterogeneous set of DNNs where each DNN has varying computational needs and thus different training rate and convergence speed. This paper proposes FLEET, a flexible ensemble DNN training framework for efficiently training a heterogeneous set of DNNs. We build FLEET via several technical innovations. We theoretically prove that an optimal resource allocation is NP-hard and propose a greedy algorithm to efficiently allocate resources for training each DNN with data sharing. We integrate data-parallel DNN training into ensemble training to mitigate the differences in training rates and introduce checkpointing into this context to address the issue of different convergence speeds. Experiments show that FLEET significantly improves the training efficiency of DNN ensembles without compromising the quality of the result.

Guan, Hui↗

DOE OSTI2025

Integrated Radio Frequency and Ultrasonics with Conventional Processes for Efficient Water Removal in Pulp and Paper and Other Biomaterial Applications

Conventional drying processes used in the pulp and paper industry primarily involve lengthy, surface based, multi-cylinder conductive and convective drying with low thermal efficiencies and often use some fossil-based energy. Integration of cross cutting, electrically-powered, volumetric drying process intensification technologies based on Radio Frequency (RF) and acoustics (Ultrasonics) (US) will directly impart energy into the biomaterials resulting in improved energy efficiency and throughput. Integration of RFUS-based drying technology is expected to enable U.S. manufacturing industry to reduce capital and operating costs, energy consumption, and carbon emissions while increasing energy efficiency and throughput, improving product quality and sustainability, and helping preserve U.S. manufacturing jobs. The hybrid drying approach incorporates directed radio frequency (RF) and ultrasonic (US) energy with conventional conduction, diffusion and convective heat and mass transfer overcoming the limitations of the conventional drying processes and that meets/exceeds the minimum goals. We have shown the effective removal of free and bound water in the biomaterials by leveraging the synergies of RF and US technologies integrated with conventional manufacturing processes.

42 ENGINEERING↗

DOE OSTI2025

Opportunities for iron and steel industrial wastewater treatment and reuse in the United States

Concerns around water security in the United States have heightened the interest in industrial water treatment and reuse to improve water efficiency and operational reliability. Alongside nationwide efforts to expand industrial capacity, primary manufacturing sectors are adopting more resource-efficient technologies. This transition is expected to shift industrial water consumption patterns, driving the need for improved treatment and reuse practices. This study investigates opportunities for water use, treatment, and reuse in the iron and steel sector through a review of academic and industry literature and interviews with industry representatives. It identifies key challenges in water and wastewater management and outlines the conditions under which innovative treatment technologies could be deployed. Based on these insights, the study presents a practical water management action plan. Furthermore, it assesses water quality targets across different process operations, evaluates existing treatment technologies, and highlights challenges and opportunities for improvement relative to future performance expectations. Although water is often perceived as a low-cost commodity, industry feedback suggests that improvements in water use and treatment efficiency are typically prioritized only when they also reduce energy use, carbon emissions, or costs. This study advocates for a direct two-way partnership between industry and research audiences to bring their attention toward sustainable industrial water use, treatment, and reuse.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2024

Industrial Assessment Center

Established in 1990, San Diego State University’s (SDSU) Industrial Assessment Center (IAC) is proud of its years of service. During this period, it has served over 620 small and medium-sized manufacturing plants in Southern California. SDSU/IAC’s efforts to transfer state-of-the-art technologies to industry have increased revenues, cultivated creativity, improved energy efficiencies, and benefited the environment. The Center has contributed to the region's economic growth and stability by assisting small and medium size companies to better compete in the global market. It has helped mitigate climate change by reducing greenhouse gas emissions. IAC activities have fostered productive relationships between the University and local industry, assisted industrial sectors to improve their energy efficiency and enhance their manufacturing productivity, in turn impacting the material and working conditions of their employees. In addition to financial savings and environmental benefits, we have trained tens of students who became energy specialists in various companies. Thus, a substantial benefit of the IAC has been the ongoing training of engineering faculty and students. All IAC graduates were offered jobs before or within weeks of their graduation. The activities of the SDSU/IAC have expanded the institutional expertise of the College and improved the knowledge base of the faculties involved leading to several related publications, master’s theses, and senior student projects. Significant number of peer-reviewed publications of the IAC director at SDSU have greatly benefitted from the experience of the Center. As a result of this extensive exposure to manufacturing processes, the SDSU/IAC has grown to be an integral component of SDSU’s engineering research and training. We have successfully built upon these established achievements and academic excellence. IAC service to industry is particularly vital in Southern California, a region with one of the highest manufacturing concentrations in the country. SDSU/IAC has understood and implemented the overall objectives of DOE’s IAC program and guidelines except for the pandemic years when the country’s manufacturing sector was put in dire stress. In addition to student training and service to industry, IAC’s contribution to state and local governments as well as utility companies to assess energy policies and design rebate and incentive strategies cannot be undermined.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2021

Fundamental Understanding of Cu-zeolite SCR Catalyst Aging Mechanism (CRADA 452)

The CRADA between Cummins and Pacific Northwest National Laboratory (PNNL) will focus on advanced emission control for high-efficiency engines. It will specifically focus on the following three areas: 1. Passive NOx absorbers - The purpose is to develop next generation materials that can be efficiently used to address the cold-operation, as driven by improved engine efficiency. 2. Oxidation of methane and short alkanes – The purpose is to address cold-operation emissions arising from CNG vehicles. 3. Improved understanding of particulates–the purpose is to understand how particulates are formed which will be used to develop strategies to address the tightening regulations and their enforcement for exhaust particulate matter. The first two areas will be based on PNNL’s technical leadership in the area of zeolite-based materials. The third area will have a shorter time scope to leverage the unique SPLAT capabilities at PNNL to help address Cummins’ needs in improving the understanding of particulates.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2024

Advanced Emission Control for High-Efficiency Engines

The CRADA between Cummins and Battelle will focus on: advanced emission control for high-efficiency engines. It will specifically focus on the following three areas: 1. Passive NOx absorbers - The purpose is to develop next generation materials that can be efficiently used to address the cold-operation, as driven by improved engine efficiency. 2. Oxidation of methane and short alkanes – The purpose is to address cold-operation emissions arising from CNG vehicles. 3. Improved understanding of particulates – The purpose is to understand how particulates are formed which will be used to develop strategies to address the tightening regulations and their enforcement for exhaust particulate matter. The first two areas will be based on PNNL’s technical leadership in the area of zeolite-based materials. The third area will have a shorter time scope to leverage the unique SPLAT capabilities at PNNL to help address Cummins’ needs in improving the understanding of particulates

02 PETROLEUM↗

DOE OSTI2024

Developing a new ethylene glycol/H 2 O pretreatment system to achieve efficient enzymatic hydrolysis of sugarcane bagasse cellulose and recover highly active lignin: Countercurrent extraction

Improving pretreatment efficiency is a critical premise in achieving efficient biomass conversion, and obtaining high-performance natural polymers is the guarantee of high-value conversion of biomass. Here, in this study, a new pilot-scale continuous countercurrent pretreatment reaction unit about ethylene glycol-alkali solution was designed for pretreating sugarcane bagasse in order to achieve efficient separation of the three major components of lignocellulose when expanding the scale of pretreatment, reduce lignin deposition on the fiber surface, and obtain highly active lignin and excellent enzymatic hydrolysis efficiency of cellulose. X-ray diffractometer (XRD), X-ray photoelectron spectrometer (XPS), brunauer-emmett-teller (BET) and scanning electron microscope (SEM) methods are used to analyze the structural properties of sugarcane bagasse before and after pretreatment, and high-performance liquid chromatography (HPLC) is used to analyze the monosaccharide components in the enzymatic solution. In addition, the structural properties of the recovered lignin are analyzed by gel permeation chromatography (GPC), 31 P NMR and 2D-HSQC-NMR methods. The results indicate that the system can gain a high cellulose recovery of 92.99% along with a lignin removal of 95.33%, and recovered lignin has low lignin carbohydrate complexes, low condensation, and rich in phenolic hydroxyl groups for 1.95 mmol/g. Meanwhile, the countercurrent pretreatment system can effectively reduce the deposition of lignin on the cellulose surface, which is evidently superior to the non-countercurrent pretreatment and facilitates the efficiency of enzymatic saccharification of substrate, achieving a high glucose yield of 99% as well as a total sugar yield of 91.11%. The method efficiently separates biomass in a green manner, and solid residues are easily hydrolyzed, showing potential for industrial-scale production.

09 BIOMASS FUELS↗

DOE OSTI2025

Better Climate Challenge Working Groups Non-Energy Benefits of Energy Projects-Improving Financial Payback

Energy efficiency is a key strategy recently identified by the United States Department of Energy as a pillar of industrial decarbonization. For manufacturing companies, improving energy efficiency will reduce money spent on energy utilities such as gas, electricity, and oil. Energy improvement projects also provide valuable benefits outside of simple operating cost reductions, such as reducing the carbon footprint, improving safety metrics and even enhancing quality and productivity. Unfortunately, energy efficiency projects have typically faced an adoption gap, even when they meet criteria such as payback period for capital projects. The inclusion and quantification of non-energy benefits (NEBs), also known as co-benefits, in the decision-making process for energy efficiency projects can improve the overall financial payback periods for those projects as well as potentially improve the company's key performance metrics aligned with business strategies. There are no readily available tools that facilitate this, however, and the most used tools for energy audits address NEBs in a perfunctory way if at all. We integrated research for finding and quantifying non-energy benefits of energy efficiency projects into a commonly recognized continuous improvement practice, the Define, Measure, Analyze, Improve and Control (DMAIC) Process. This process, along with software and supplemental materials, guides energy assessments to find and to quantify NEBs associated with energy conservation opportunities. Our aim is to deliver an easy to use and effective process and software tool and to maximize return on investment for energy efficiency projects as well as contribute to companies' strategic performance goals.

DMAIC↗

DOE OSTI2025

High aspect ratio organic light-emitting diodes

Reliability is particularly challenging for organic light-emitting diodes (OLEDs) used in solid-state lighting applications, because OLED lifetime is inversely proportional to luminance, and most lighting applications demand high luminance. Here we introduce a strategy to overcome this tradeoff by constructing OLEDs on a substrate with sub-mm, high aspect ratio surface texture. By creating more active OLED area per unit lighting panel area, the device current density required to generate a given panel luminance decreases. We validate this approach for fluorescent and phosphorescent OLEDs, demonstrating good thickness uniformity on corrugated substrates with area enhancement factors up to 1.4x using a standard thermal evaporator. Relative to planar controls at the same panel current density, the high aspect ratio devices achieve a 2.7-fold increase in operating lifetime and up to a 40% increase in external light extraction efficiency, indicating that this approach offers a powerful pathway to improve the efficiency and lifetime of OLED lighting.

OLED↗

DOE OSTI2020

Reduced Petroleum Use Through Easily Reformed Fuels and Dedicated Exhaust Gas Recirculation

This project was proposed to demonstrate a >25% reduction in petroleum usage for a light duty SI vehicle by synergistically combining the Dedicated EGR combustion system developed at SwRI with modified fuel formulations incoroporating biofuel components. Typically, a D-EGR engine yields a 10% gain in fuel efficiency relative to the base engine through a combination of improved thermodynamic efficiency from the EGR application and the significant increase in compression ratio realized through the knock reduction benefits of EGR and hydrogen addition. As the D-EGR performance is strongly linked to hydrogen production, the proposal team anticipated that gasoline formulation changes could enhance the hydrogen production rate relative to a conventional gasoline. This was expected to provide additional efficiency gains to the engine. The final step of incorporating biofuel components would then yield a final result meeting the >25% petroleum reduction target.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2025

Dimolybdenum Paddlewheel Complexes with Cation Binding Sites as Electrolyte Additives to Manipulate the Solid-Electrolyte Interphase at Lithium Metal Anodes

The use of electrolyte additives at millimolar loadings to control the surface chemistry of lithium metal anodes (LMAs) is a leading strategy to improve lithium metal batteries and promote electrosynthetic reactions. Whereas previous studies employed either inorganic or organic additives, in this study, we report the first organometallic additive, Mo 2 (mea) 4 [1, mea = 2-(2-methoxyethoxy)acetate], a dimolybdenum paddlewheel complex that is stable under Li plating conditions and features cation binding sites in the second coordination sphere that promote reversible Li + coordination. Binding of Li + ions to 1 induces immobilization of cationically charged aggregates (or products thereof) into the solid electrolyte interphase (SEI), imparting multiple beneficial functions. The modified SEI was found to protect the LMA against parasitic side reactions, produce modest but measurable improvements to Li plating properties (e.g., overpotential, surface structure, and Coulombic efficiency), and improve interfacial charge transport properties. Furthermore, the most notable benefit to battery cycling performance appears in calendar aging tests, which show that the presence of the additive protects the LMA from parasitic side reactions that would otherwise decrease overall cell cycling efficiency over time. Collectively, these data disclose a tactic for designing electrolyte additives using principles of organometallic synthesis.

Additives↗

DOE OSTI2020

Analysis of Space-Conditioning Loads in Commercial Buildings

Space conditioning end-uses, which include heating, cooling, and ventilation, represent a significant fraction of commercial building energy use, with a wide variety of heating and cooling technology options available in the market. In the interest of improving the overall efficiency of heating, ventilation and air-conditioning (HVAC) technologies, governments, utilities and private sector entities have implemented a variety of market transformation policies that aim to influence consumer purchase decisions. To evaluate the costs and benefits of such programs, analysts typically postulate a hypothetical default equipment choice, and compare it to one that provides comparable service with lower energy and/or power use. The corresponding reduced operating cost provides a benefit that offsets the potential higher cost of improved efficiency. Typically, life-cycle cost or cash-flow analyses are used to quantify the net economic benefit. These analyses require the capability to assess how a given equipment design would perform across a broad range of characteristics, both of the building and of the local weather. While these assessments can be performed using customized building simulations, it is generally not practical to develop and validate detailed building simulation code to cover all the potential variations of equipment design and installation. An alternative, and somewhat simpler, approach is to solely use detailed building simulations to generate time series of heating and cooling loads in commercial buildings. These loads can then be used as input to more detailed, stand-alone engineering models that simulate HVAC system performance under different equipment designs. This approach was used to evaluate a range of high-efficiency commercial packaged air conditioner design options for the Department of Energy’s Appliance and Equipment Standards Program (DOE-EERE 2015). While there may be some loss of precision relative to full simulation, the accuracy of this approach is sufficient for practical applications of cost-benefit analysis. This report describes the development of a database of commercial building heating and cooling loads, generated using the EnergyPlus software package, a whole building energy use model supported by the Department of Energy (DOE-EERE 2020a). EnergyPlus takes as input a set of configuration files that describe the building itself (size, zoning, envelope characteristics, etc.) and the various systems within it (HVAC, lighting, water heating, etc.). This analysis uses a publicly available collection of commercial reference buildings (CRB), comprised of sixteen building types and three vintages (DOE-EERE 2020b; Deru et al 2011). Each building is simulated in eighteen different locations, covering a wide range of climatic conditions. The prototype building description files assign the type of HVAC equipment used, and capacities across climate zones.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2021

US building energy efficiency and flexibility as an electric grid resource

Buildings consume 75% of U.S. electricity; therefore, improving the efficiency and flexibility of building operations could increase the reliability and resilience of the rapidly-changing electricity system. We estimate the technical potential near- and long-term impacts of best available building efficiency and flexibility measures on annual electricity use and hourly demand across the contiguous U.S. Co-deployment of building efficiency and flexibility avoids up to 742 TWh of annual electricity use and 181 GW of daily net peak load in 2030, rising to 800 TWh and 208 GW by 2050; at least 59 GW and 69 GW of the peak reductions are dispatchable. Implementing efficiency measures alongside flexibility measures reduces the potential for off-peak load increases, underscoring limitations on load shifting in efficient buildings. Overall, however, we find a substantial building-grid resource that could reduce future fossil-fired generation needs while also reducing dependence on energy storage with increasing variable renewable energy penetration.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2025

Reconfigurable neuromorphic components and algorithms for next-generation artificial intelligence

Digital transistor-based general-purpose hardware (e.g., central processing units) is the dominant solution to support both traditional computing (logic, arithmetic, etc.) as well as modern artificial intelligence. State-of-the-art research has shown feasibility of post-digital physics-based neuromorphic hardware, which is hypothesized to support artificial intelligence algorithms with orders-of-magnitude improved time/energy efficiencies. But such research has not been widely deployed mainly because of such novel hardware’s extreme application-specificity, and the dominance of low-cost general-purpose (but inefficient) digital hardware. To make use of the novel algorithms and the superlative performance of physics-based hardware, we need to identify scientific principles that can enable generality in physics-based hardware. This work resulted in two important broad outcomes – first, we demonstrate fully reconfigurable neuromorphic components, and second, we demonstrate a viable artificial intelligence learning algorithm that can exploit the functioning of neuromorphic hardware. We demonstrate up to five orders of magnitude improvement in energy efficiency compared to the best general-purpose digital hardware.

97 MATHEMATICS AND COMPUTING↗