Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Program Optimization”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,207 records · Page 67
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Design of voice coil motor dynamic focusing unit for a laser scanner

Laser scanning systems have been used for material processing tasks such as welding, cutting, marking, and drilling. However, applications have been limited by the small range of motion and slow speed of the focusing unit, which carries the focusing optics. To overcome these limitations, a dynamic focusing system with a long travel range and high speed is needed. In this study, a dynamic focusing unit for a laser scanning system with a voice coil motor (VCM) mechanism is proposed to enable fast speed and a wide focusing range. The VCM has finer precision and higher speed than conventional step motors and a longer travel range than earlier lead zirconium titanate actuators. The system has a hollow configuration to provide a laser beam path. This also makes it compact and transmission-free and gives it low inertia. The VCM's magnetics are modeled using a permeance model. Its design parameters are determined by optimization using the Broyden–Fletcher–Goldfarb–Shanno method and a sequential quadratic programming algorithm. After the VCM is designed, the dynamic focusing unit is fabricated and assembled. The permeance model is verified by a magnetic finite element method simulation tool, Maxwell 2D and 3D, and by measurement data from a gauss meter. The performance is verified experimentally. The results show a resolution of 0.2 μm and travel range of 16 mm. These are better than those of conventional focusing systems; therefore, this focusing unit can be applied to laser scanning systems for good machining capability.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Suppressing Structural Relaxation in Nanoscale Antimony to Enable Ultralow‐Drift Phase‐Change Memory Applications

Abstract Phase‐change random‐access memory (PCRAM) devices suffer from pronounced resistance drift originating from considerable structural relaxation of phase‐change materials (PCMs), which hinders current developments of high‐capacity memory and high‐parallelism computing that both need reliable multibit programming. This work realizes that compositional simplification and geometrical miniaturization of traditional GeSbTe‐like PCMs are feasible routes to suppress relaxation. While to date, the aging mechanisms of the simplest PCM, Sb, at nanoscale, have not yet been unveiled. Here, this work demonstrates that in an optimal thickness of only 4 nm, the thin Sb film can enable a precise multilevel programming with ultralow resistance drift coefficients, in a regime of ≈10 −4 –10 −3 . This advancement is mainly owed to the slightly changed Peierls distortion in Sb and the less‐distorted octahedral‐like atomic configurations across the Sb/SiO 2 interfaces. This work highlights a new indispensable approach, interfacial regulation of nanoscale PCMs, for pursuing ultimately reliable resistance control in aggressively‐miniaturized PCRAM devices, to boost the storage and computing efficiencies substantially.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Programming Abstractions for Managing Workflows on Tiered Storage Systems

Scientific workflows in High Performance Computing (HPC) environments are processing large amounts of data. The storage hierarchy on HPC systems is getting deeper, driven by new technologies (NVRAMs, SSDs, etc.) There is a need for new programming abstractions that allow users to seamlessly manage data at the workflow level on multi-tiered storage systems, and provide optimal workflow performance and use of storage resources. In previous work, we introduced a software architecture Managing Data on Tiered Storage for Scientific Workflows (MaDaTS) that used a Virtual Data Space (VDS) abstraction to hide the complexities of the underlying storage system while allowing users to control data management strategies. In this article, we detail the data-centric programming abstractions that allow users to manage a workflow around its data on the storage layer. The programming abstractions simplify data management for scientific workflows on multi-tiered storage systems, without affecting workflow performance or storage capacity. We measure the overheads and effectiveness introduced by the programming abstractions of MaDaTS. Our results show that these abstractions can optimally use the storage capacity in lesser capacity storage tiers, and simplify data management without adding any performance overheads.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2025

Benefits of Dual Fuel Heat Pump Grid-responsive Control: A Model-based Control Optimization Approach Using Building and Equipment Co-simulation

Conventional dual fuel heat pumps lack the intelligent control mechanisms to efficiently manage the switch between heat pump and furnace, leading to sub-optimal energy usage and, in some cases, increased operating costs. To resolve this gap, this study applies optimized control on hybrid heat pumps. With a focus on equipment control strategies, we compare the performances of five spacing heating equipment, including a conventional heat pump (HP), a conventional furnace, a dual fuel heat pump (DFHP) with conventional control, a dual fuel heat pump with smart control, and a novel seamlessly fuel flexible heat pump (SFFHP). While DFHP runs on either gas or electricity at any given moment, SFFHP concurrently consumes gas and electricity by continuously optimizing the proportion of each. In this research, a co-simulation framework is developed by integrating a building envelope model with a physics-based heat pump simulation model to analyze the benefits of grid-responsive controls of DFHP and SFFHP. The model-based optimal controls adjust the operation of the heat pump and gas furnace based on utility price signals and marginal grid emission to minimize utility cost and CO 2 emissions for multiple climate zones, different utility tariffs, and marginal grid emission scenarios. Case studies in Chicago and Los Angeles demonstrate that SFFHP and DFHP, with model-based optimal control, can deliver significant reductions in peak demand, utility cost, and CO 2 emission. In Chicago, SFFHP and smart controlled DFHP yield up to 64.7% and 61.7% utility cost reduction and up to 15.7% and 8.5% CO 2 emission reduction compared to the gas furnace. In Los Angeles, SFFHP and smart controlled DFHP achieve up to 43.6% and 40.1% utility cost reduction and up to 13.8% and 14.1% CO2 emission reduction compared to conventional heat pumps. In conclusion, by leveraging the fuel flexibility nature of dual fuel heat pumps, the model-based control optimization approach makes dual fuel heat pump an attractive option for demand response programs.

Control↗
DOE OSTI2015

SU-E-T-562: Motion Tracking Optimization for Conformal Arc Radiotherapy Plans: A QUASAR Phantom Based Study

Purpose: This study is to use plan parameters optimization (Dose rate, collimator angle, couch angle, initial starting phase) to improve the performance of conformal arc radiotherapy plans with motion tracking by increasing the plan performance score (PPS). Methods: Two types of 3D conformal arc plans were created based on QUASAR respiratory motion phantom with spherical and cylindrical targets. Sinusoidal model was applied to the MLC leaves to generate motion tracking plans. A MATLAB program was developed to calculate PPS of each plan (ranges from 0–1) and optimize plan parameters. We first selected the dose rate for motion tracking plans and then used simulated annealing algorithm to search for the combination of the other parameters that resulted in the plan of the maximal PPS. The optimized motion tracking plan was delivered by Varian Truebeam Linac. In-room cameras and stopwatch were used for starting phase selection and synchronization between phantom motion and plan delivery. Gaf-EBT2 dosimetry films were used to measure the dose delivered to the target in QUASAR phantom. Dose profiles and Truebeam trajectory log files were used for plan delivery performance evaluation. Results: For spherical target, the maximal PPS (PPSsph) of the optimized plan was 0.79: (Dose rate: 500MU/min, Collimator: 90°, Couch: +10°, starting phase: 0.83π). For cylindrical target, the maximal PPScyl was 0.75 (Dose rate: 300MU/min, Collimator: 87°, starting phase: 0.97π) with couch at 0°. Differences of dose profiles between motion tracking plans (with the maximal and the minimal PPS) and 3D conformal plans were as follows: PPSsph=0.79: %ΔFWHM: 8.9%, %Dmax: 3.1%; PPSsph=0.52: %ΔFWHM: 10.4%, %Dmax: 6.1%. PPScyl=0.75: %ΔFWHM: 4.7%, %Dmax: 3.6%; PPScyl=0.42: %ΔFWHM: 12.5%, %Dmax: 9.6%. Conclusion: By achieving high plan performance score through parameters optimization, we can improve target dose conformity of motion tracking plan by decreasing total MLC leaf travel distance and leaf speed.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2021

A solution framework for linear PDE-constrained mixed-integer problems

Abstract We present a general numerical solution method for control problems with state variables defined by a linear PDE over a finite set of binary or continuous control variables. We show empirically that a naive approach that applies a numerical discretization scheme to the PDEs to derive constraints for a mixed-integer linear program (MILP) leads to systems that are too large to be solved with state-of-the-art solvers for MILPs, especially if we desire an accurate approximation of the state variables. Our framework comprises two techniques to mitigate the rise of computation times with increasing discretization level: First, the linear system is solved for a basis of the control space in a preprocessing step. Second, certain constraints are just imposed on demand via the IBM ILOG CPLEX feature of a lazy constraint callback. These techniques are compared with an approach where the relations obtained by the discretization of the continuous constraints are directly included in the MILP. We demonstrate our approach on two examples: modeling of the spread of wildfire and the mitigation of water contamination. In both examples the computational results demonstrate that the solution time is significantly reduced by our methods. In particular, the dependence of the computation time on the size of the spatial discretization of the PDE is significantly reduced.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

JHR Project: a future Material Testing Reactor working as an International user Facility: The key-role of instrumentation in support to the development of modern experimental capacity

Research and development on fuel and material behaviour under irradiation is a key issue for sustainable nuclear energy in order to meet specific needs by keeping the best level of safety. These needs mainly deal with a constant improvement of performances and safety in order to optimize the fuel cycle and hence to reach nuclear energy sustainable objectives. A sustainable nuclear energy requires a high level of performances in order to meet specific needs such as: - Pursuing improvement of the performances and safety of present and coming water cooled reactor technologies. This will require a continuous R and D support following a long-term trend driven by the plant life management, safety demonstration, flexibility and economics improvement. Experimental irradiations of structure materials are necessary to anticipate these material behaviours and will contribute to their optimisation. - Upgrading continuously nuclear fuel technology in present and future nuclear power plants to achieve better performances and to optimise the fuel cycle keeping the best level of safety. Fuel evolution for generation II, III and III+ is a key stake requiring developments, qualification tests and safety experiments to ensure the competitiveness and safety: experimental tests exploring the full range of fuel behaviour determine fuel stability limits and safety margins, as a major input for the fuel reliability analysis. To perform such accurate and innovative progress and developments, specific and ad hoc instrumentation, irradiation devices, measurement methods are necessary to be set up inside or beside the material testing reactor (MTR) core. These experiments require beforehand in situ and on line sophisticated measurements to accurately determine different key parameters such as thermal and fast neutron fluxes and nuclear heating in order to precisely monitor and control the conducted assays. The new Material Testing Reactor JHR (Jules Horowitz Reactor) currently under construction at CEA Cadarache research centre in the south of France will represent a major Research Infrastructure for scientific studies regarding material and fuel behavior under irradiation. It will also be devoted to medical isotopes production. Hence JHR will offer a real opportunity to perform R and D programs regarding needs above and hence will crucially contribute to the selection, optimization and qualification of these innovative materials and fuels. The JHR reactor objectives, principles and main characteristics associated to specific experimental devices associated to measurement techniques and methodology, their performances, their limitations and field of applications will be presented and discussed. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2016

Frame average optimization of cine-mode EPID images used for routine clinical in vivo patient dose verification of VMAT deliveries

Purpose: The in vivo 3D dose delivered to a patient during volumetric modulated arc therapy (VMAT) delivery can be calculated using electronic portal imaging device (EPID) images. These images must be acquired in cine-mode (i.e., “movie” mode) in order to capture the time-dependent delivery information. The angle subtended by each cine-mode EPID image during an arc can be changed via the frame averaging number selected within the image acquisition software. A large frame average number will decrease the EPID’s angular resolution and will result in a decrease in the accuracy of the dose information contained within each image. Alternatively, less EPID images acquired per delivery will decrease the overall 3D patient dose calculation time, which is appealing for large-scale clinical implementation. Therefore, the purpose of this study was to determine the optimal frame average value per EPID image, defined as the highest frame averaging that can be used without an appreciable loss in 3D dose reconstruction accuracy for VMAT treatments. Methods: Six different VMAT plans and six different SBRT-VMAT plans were delivered to an anthropomorphic phantom. Delivery was carried out on a Varian 2300ix model linear accelerator (Linac) equipped with an aS1000 EPID running at a frame acquisition rate of 7.5 Hz. An additional PC was set up at the Linac console area, equipped with specialized frame-grabber hardware and software packages allowing continuous acquisition of all EPID frames during delivery. Frames were averaged into “frame-averaged” EPID images using MATLAB. Each frame-averaged data set was used to calculate the in vivo dose to the patient and then compared to the single EPID frame in vivo dose calculation (the single frame calculation represents the highest possible angular resolution per EPID image). A mean percentage dose difference of low dose (<20% prescription dose) and high dose regions (>80% prescription dose) was calculated for each frame averaged scenario for each plan. The authors defined their unacceptable loss of accuracy as no more than a ±1% mean dose difference in the high dose region. Optimal frame average numbers were then determined as a function of the Linac’s average gantry speed and the dose per fraction. Results: The authors found that 9 and 11 frame averages were suitable for all VMAT and SBRT-VMAT treatments, respectively. This resulted in no more than a 1% loss to any of the dose region’s mean percentage difference when compared to the single frame reconstruction. The optimized number was dependent on the treatment’s dose per fraction and was determined to be as high as 14 for 12 Gy/fraction (fx), 15 for 8 Gy/fx, 11 for 6 Gy/fx, and 9 for 2 Gy/fx. Conclusions: The authors have determined an optimal EPID frame averaging number for multiple VMAT-type treatments. These are given as a function of the dose per fraction and average gantry speed. These optimized values are now used in the authors’ clinical, 3D, in vivo patient dosimetry program. This provides a reduction in calculation time while maintaining the authors’ required level of accuracy in the dose reconstruction.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2016

Solution of monotone complementarity and general convex programming problems using a modified potential reduction interior point method

We present a homogeneous algorithm equipped with a modified potential function for the monotone complementarity problem. We show that this potential function is reduced by at least a constant amount if a scaled Lipschitz condition (SLC) is satisfied. A practical algorithm based on this potential function is implemented in a software package named iOptimize. The implementation in iOptimize maintains global linear and polynomial time convergence properties, while achieving practical performance. It either successfully solves the problem, or concludes that the SLC is not satisfied. When compared with the mature software package MOSEK (barrier solver version 6.0.0.106), iOptimize solves convex quadratic programming problems, convex quadratically constrained quadratic programming problems, and general convex programming problems in fewer iterations. Moreover, several problems for which MOSEK fails are solved to optimality. In addition, we also find that iOptimize detects infeasibility more reliably than the general nonlinear solvers Ipopt (version 3.9.2) and Knitro (version 8.0).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Mathematical Programming Models for Shale Oil & Gas Development: A Review and Perspective

Here, in this paper, we provide a comprehensive review of mathematical programming models for shale oil & gas development, and we offer a perspective on outstanding research opportunities. We distinguish contributions in five major topic areas, namely: (1) development planning, (2) water management, (3) production optimization, (4) supplies, gathering & processing, and (5) life cycle analysis & sustainability. We highlight how various types of mathematical programming models (i.e., linear programs, nonlinear programs, mixed-integer linear programs, mixed-integer nonlinear programs) have been proposed primarily by the Process Systems Engineering community to address the respective decision-making problems, and we highlight instances of successful deployment in industry. Finally, based on a critical assessment of the existing body of work, we identify opportunities for future research across the major topic areas.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Tough Errors Are no Match (TEAM): Optimizing the Quantum Compiler for Noise Resilience

This report summarizes research performed under the Tough Errors Are no Match (TEAM) project. The primary focus of TEAM has been to research and develop a compilation toolbox leveraging techniques from quantum characterization and control, probabilistic programming, and approximate computing. Our goal was to develop robust protocols that can be integrated into quantum compilers to optimize and enhance the robustness of noisy computation. Here, we provide a summary of TEAM work focused on characterization and control of quantum systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Groundwater Monitoring Optimization of Post Closure Waste Sites at SRS - 13184

Groundwater monitoring at the Savannah River Site (SRS) is required at dozens of waste sites and includes sampling at over 1,000 monitoring wells. The expected longevity of groundwater contamination and associated groundwater monitoring and reporting constitutes a significant long-term cost that represents an increasing proportion of the environmental management budget as surface waste units are closed. Therefore, a comprehensive evaluation of the monitoring program for eighteen regulated waste units was conducted to identify areas where monitoring could be optimized. The units evaluated varied considerably in the scope of monitoring; ranging from two wells to hundreds of wells. In order to systematically evaluate such disparate monitoring networks, SRS developed a decision-logic analysis using flow sheets to address potential areas of optimization. Five areas were identified for evaluation, including: (1) Comparison of current monitoring to regulatory requirements, (2) Spatial distribution, (3) Temporal sampling, (4) Analyte requirements, and (5) Reporting frequency and content. Optimization recommendations were made for fifteen of the eighteen groundwater units. The spatial evaluation resulted in recommendations to suspend sampling in 79 wells and add sampling at 16 wells. The temporal evaluation resulted in recommendations to reduce the number of well visits per year by 504. Analyte reductions were recommended at three groundwater units, with increases at three other units. Reporting frequency reductions were recommended for five units. Approximately $700,000 (direct dollars) of potential annualized cost savings were identified for these groundwater units, provided all recommendations are approved. The largest area of savings was associated with reducing the reporting frequency. The optimization approach has been presented to the EPA and South Carolina Department of Environmental Control (SCHDEC), with unit-specific recommendations approved for all five units presented. This approach can be expected to be highly successful for sites with rich historical data sets and where the requirements in regulatory monitoring plans can be negotiated. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Real-Time Ecodriving Control in Electrified Connected and Autonomous Vehicles Using Approximate Dynamic Programing

Connected and automated vehicles (CAVs), particularly those with a hybrid electric powertrain, have the potential to significantly improve vehicle energy savings in real-world driving conditions. In particular, the ecodriving problem seeks to design optimal speed and power usage profiles based on available information from connectivity and advanced mapping features to minimize the fuel consumption over an itinerary. This paper presents a hierarchical multilayer model predictive control (MPC) approach for improving the fuel economy of a 48 V mild-hybrid powertrain in a connected vehicle environment. Approximate dynamic programing (DP) is used to solve the receding horizon optimal control problem, whose terminal cost is approximated with the base policy obtained from the long-term optimization. The controller was tested virtually (with deterministic and Monte Carlo simulation) across multiple real-world routes, demonstrating energy savings of more than 20%. The controller was then deployed on a test vehicle equipped with a rapid prototyping embedded controller. In-vehicle testing confirm the energy savings obtained in simulation and demonstrate the real-time ability of the controller.

Automation & Control Systems↗
DOE OSTI2018

Verification and Validation of Optimization of Replacement Portal Monitoring Replay Tools

The Los Alamos National Laboratory and the Johns Hopkins Applied Physics Laboratory (APL) are both developing optimization software to fulfill the objective of Phase III of the Replacement Portal Monitoring (RPM) Program for the Department of Homeland Security. The objective of the Phase III of the RPM Program is to conduct an evaluation of three RPM systems designed to enhance mission effectiveness, gain operational efficiencies, and to address emerging mission needs against the Countering Weapons of Mass Destruction (CWMD ) nuclear threat basis and special nuclear material (SNM) used in performance testing. As such this task involves the use of global optimization algorithms.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2020

Enabling Highly Efficient Capsule Networks Processing Through A PIM-Based Architecture Design

In recent years, the CNNs have achieved great successes in the image processing tasks, e.g., image recognition and object detection. Unfortunately, traditional CNN's classication is found to be easily misled by increasingly complex image features due to the usage of pooling operations, hence unable to preserve accurate position and pose information of the objects. To address this challenge, a novel neural network structure called Capsule Network has been proposed, which introduces equivariance through capsules to signicantly enhance the learning ability for image segmentation and object detection. Due to its requirement of performing a high volume of matrix operations, CapsNets have been generally accelerated on modern GPU platforms that provide highly optimized software library for common deep learning tasks. However, based on our performance characterization on modern GPUs, CapsNets exhibit low effciency due to the special program and execution features of their routing procedure, including massive unshareable intermediate variables and intensive syn- chronizations, which are very dicult to optimize at software level. To address these challenges, we propose a hybrid computing architecture design named PIM-CapsNet. It preserves GPU's on-chip computing capability for accelerating CNN types of layers in CapsNet, while pipelining with an off-chip in-memory acceleration solution that effectively tackles routing procedure's ineffciency by leveraging the processing-in-memory capability of today's 3D stacked memory. Using routing procedure's inherent parallellization feature, our design enables hierarchical improvements on CapsNet inference effciency through minimizing data movement and maximizing parallel processing in memory. Evaluation results demonstrate that our proposed design can achieve substantial improvement on both performance and energy savings for CapsNet inference, with almost zero accuracy loss. The results also suggest good performance scalability in optimizing the routing procedure with increasing network size.

Zhang, Xingyao↗
DOE OSTI2016

Optimization-based mesh correction with volume and convexity constraints

Here, we consider the problem of finding a mesh such that 1) it is the closest, with respect to a suitable metric, to a given source mesh having the same connectivity, and 2) the volumes of its cells match a set of prescribed positive values that are not necessarily equal to the cell volumes in the source mesh. Also, this volume correction problem arises in important simulation contexts, such as satisfying a discrete geometric conservation law and solving transport equations by incremental remapping or similar semi-Lagrangian transport schemes. In this paper we formulate volume correction as a constrained optimization problem in which the distance to the source mesh defines an optimization objective, while the prescribed cell volumes, mesh validity and/or cell convexity specify the constraints. We solve this problem numerically using a sequential quadratic programming (SQP) method whose performance scales with the mesh size. To achieve scalable performance we develop a specialized multigrid-based preconditioner for optimality systems that arise in the application of the SQP method to the volume correction problem. Numerical examples illustrate the importance of volume correction, and showcase the accuracy, robustness and scalability of our approach.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

Optimization and testing results of Zr-bearing ferritic steels

The mission of the Nuclear Energy Enabling Technologies (NEET) program is to develop crosscutting technologies for nuclear energy applications. Advanced structural materials with superior performance at elevated temperatures are always desired for nuclear reactors, which can improve reactor economics, safety margins, and design flexibility. They benefit not only new reactors, including advanced light water reactors (LWRs) and fast reactors such as sodium-cooled fast reactor (SFR) that is primarily designed for management of high-level wastes, but also life extension of the existing fleet when component exchange is needed. Developing and utilizing the modern materials science tools (experimental, theoretical, and computational tools) is an important path to more efficient alloy development and process optimization. Ferritic-martensitic (FM) steels are important structural materials for nuclear reactors due to their advantages over other applicable materials like austenitic stainless steels, notably their resistance to void swelling, low thermal expansion coefficients, and higher thermal conductivity. However, traditional FM steels exhibit a noticeable yield strength reduction at elevated temperatures above ~500°C, which limits their applications in advanced nuclear reactors which target operating temperatures at 650°C or higher. Although oxide-dispersion-strengthened (ODS) ferritic steels have shown excellent high-temperature performance, their extremely high cost, limited size and fabricability of products, as well as the great difficulty with welding and joining, have limited or precluded their commercial applications. Zirconium has shown many benefits to Fe-base alloys such as grain refinement, improved phase stability, and reduced radiation-induced segregation. The ultimate goal of this project is, with the aid of computational modeling tools, to accelerate the development of a new generation of Zr-bearing ferritic alloys to be fabricated using conventional steelmaking practices, which have excellent radiation resistance and enhanced high-temperature creep performance greater than Grade 91.

36 MATERIALS SCIENCE↗
DOE OSTI2024

eCC++ : A Compiler Construction Framework for Embedded Domain-Specific Languages

eCC++ is a new compiler construction framework for embedding domain-specific programming languages within C++. That is, the host language is C++, the guest language is the DSL to be embedded in C++, and eCC++ is the tool that enables the embedding. The eCC++ framework is composed of three main components: a front-end, an API for program verification based on a functional and declarative intermediate representation (IR), and a Multi-Level Intermediate Representation (MLIR) code generator. The eCC++ front-end consists of a library of C++ classes and operators that can be used to define the guest language. Guest sources are compiled with any standard C++ compiler, and when run, the resulting executable generates an eCC++ IR representation of the program, which can be verified within the eCC++ framework. Finally, eCC++ allows for high-level and domain-specific optimizations before generating MLIR. In summary, eCC++ aims to act as a generic front-end that enables embedding guest languages into C++, and provides necessary compiler technology for program verification, targeting the existing capabilities in the MLIR infrastructure. The paper evaluates the eCC++ expressiveness and usability describing the process of embedding GraphIt, a high-performance graph language in C++.

Gonzalez Tallada, Marc↗