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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.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Addressing Thermal and Performance Variability Issues in Dynamic Processors

As CMOS scaling nears its end, parameter variations (process, temperature and voltage) are becoming a major concern. To overcome parameter variations and provide stability, modern processors are becoming dynamic, opportunistically adjusting voltage and frequency based on thermal and energy constraints, which negatively impacts traditional bulk-synchronous parallelism-minded hardware and software designs. As node-level architecture is growing in complexity, implementing variation control mechanisms only with hardware can be a challenging task. In this paper we investigate a software strategy to manage hardwareinduced variations, leveraging low-level monitoring/controlling mechanisms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Benefits of Integration of Aerojet Rocketdyne and RTI Advanced Gasification Technologies for Hydrogen-Rich Syngas Production

The key objective for this project was to evaluate the potential to achieve substantial reductions in the production cost of H 2 -rich syngas via coal gasification with near-zero emissions due to the cumulative and synergistic benefits realized when multiple advanced technologies are integrated into the overall conversion process. In this project, Aerojet Rocketdyne’s (AR’s) advanced gasification technology (currently being offered as R-GAS™) and RTI International’s (RTI’s) advanced warm syngas cleanup technologies were evaluated via a number of comparative techno-economic case studies. AR’s advanced gasification technology consists of a dry solids pump and a compact gasifier system. Based on the unique design of this gasifier, it has been shown to reduce the capital cost of the gasification block by between 40 and 50%. At the start of this project, actual experimental work had been demonstrated through pilot plant systems for both the gasifier and dry solids pump. RTI’s advanced warm syngas cleanup technologies consist primarily of RTI’s Warm Gas Desulfurization Process (WDP) technology, which effectively allows decoupling of the sulfur and CO 2 removal allowing for more flexibility in the selection of the CO 2 removal technology, plus associated advanced technologies for direct sulfur recovery and water gas shift (WGS). WDP has been demonstrated at pre-commercial scale using an activated amine carbon dioxide recovery process which would not have been possible if a majority of the sulfur had not been removed from the syngas by WDP. This pre-commercial demonstration of RTI’s advanced warm syngas cleanup system was conducted in parallel to the activities on this project. The technical data and cost information from this pre-commercial demonstration were extensively used in this project during the techno-economic analysis. With this project, both of RTI’s advanced WGS technologies were investigated. Because RT’s advanced fixed-bed WGS (AFWGS) process was successfully implemented in the WDP pre-commercial demonstration test mentioned above, this technology was used as part of RTI’s advanced warm syngas technology package for the techno-economic analyses for this project. RTI’s advanced transport-reactor-based WGS (ATWGS) process was still conceptual at the start of this project, but one of the tasks for this project was to evaluate the technical feasibility of this technology. In each of the three application-based comparison studies conducted as part of this project, the reference case was based on an existing Department of Energy National Energy Technology Laboratory (DOE/NETL) system study. Each of these references cases used existing commercial technology and the system resulted in > 90% carbon capture. In the comparison studies for the use of the hydrogen-rich syngas generated in either an Integrated Gasification Combined Cycle (IGCC) or a Coal-to-Methanol (CTM) plant, the comparison cases consisted of the reference case, a case with the integration of each individual advanced technology (either AR or RTI), and finally a case with the integration of all the advanced technologies (AR and RTI combined). In the Coal-to-Liquids (CTL) comparison study, the comparison study consisted of only three cases, which included a reference case, a case with just RTI’s advanced syngas cleaning technology, and a case with AR’s and RTI’s advanced technologies. The results from these comparison studies showed that the integration of the advanced technologies did result in substantial benefits, and by far the greatest benefits were achieved for cases integrating all the advanced technologies. For the IGCC study, the fully integrated case resulted in a 1.4% net efficiency improvement, an 18% reduction in capital cost per kW of capacity, a 12% reduction in the operating cost per kWh, and a 75–79% reduction in sulfur emissions. For the CTM case, the fully integrated plant resulted in a 22% reduction in capital cost, a 13% reduction in operating costs, a > 99% net reduction in sulfur emissions, and a reduction of 13–15% in CO 2 emissions. Because the capital cost represents over 60% of the methanol Required Selling Price (RSP), the significant reduction in the capital cost for the advanced technology case resulted in an 18% reduction in methanol RSP. For the CTL case, the fully integrated plant resulted in a 16% reduction in capital cost, which represented a 13% reduction in diesel RSP. Finally, the technical feasibility analysis of RTI’s ATWGS process demonstrated that a fluid-bed catalyst with sufficient attrition resistance and WGS activity could be made and that the process achieved about a 24% reduction in capital cost compared to a conventional fixed-bed commercial process.

08 HYDROGEN↗
DOE OSTI2017

On the Parallel and Oblique Firehose Instability in Fluid Models

A brief analysis of the proton parallel and oblique firehose instability is presented from a fluid perspective, and the results are compared with kinetic theory solutions obtained by the WHAMP code. It is shown that the classical CGL model very accurately describes the growth rate of these instabilities at sufficiently long spatial scales (small wavenumbers). The required stabilization of these instabilities at small spatial scales (high wavenumbers) naturally requires dispersive effects, and the stabilization is due to the Hall term and finite Larmor radius corrections to the pressure tensor. Even though the stabilization is not completely accurate, since at small spatial scales a relatively strong collisionless damping comes into effect, we find that the main concepts of the maximum growth rate and the stabilization of these instabilities is indeed present in the fluid description. However, there are differences that are quite pronounced when close to the firehose threshold, and that clarify the different profiles for marginally stable states with a prescribed maximum growth rate γ{sub max} in the simple fluid models considered here and the kinetic description.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Late Holocene evolution of a coupled, mud-dominated delta plain–chenier plain system, coastal Louisiana, USA

Abstract. Major deltas and their adjacent coastal plains are commonly linked by means of coast-parallel fluxes of water, sediment, and nutrients. Observations of the evolution of these interlinked systems over centennial to millennial timescales are essential to understand the interaction between point sources of sediment discharge (i.e. deltaic distributaries) and adjacent coastal plains across large spatial (i.e. hundreds of kilometres) scales. This information is needed to constrain future generations of numerical models to predict coastal evolution in relation to climate change and other human activities. Here we examine the coastal plain (Chenier Plain, CP) adjacent to the Mississippi River delta, one of the world's largest deltas. We use a refined chronology based on 22 new optically stimulated luminescence and 22 new radiocarbon ages to test the hypothesis that cyclic Mississippi subdelta shifting has influenced the evolution of the adjacent CP. We show that over the past 3 kyr, accumulation rates in the CP were generally 0–1 Mt yr −1 . However, between 1.2 and 0.5 ka, when the Mississippi River shifted to a position more proximal to the CP, these rates increased to 2.9 ±1.1 Mt yr −1 or 0.5–1.5 % of the total sediment load of the Mississippi River. We conclude that CP evolution during the past 3 kyr was partly a direct consequence of shifting subdeltas, in addition to changing regional sediment sources and modest rates of relative sea-level (RSL) rise. The RSL history of the CP during this time period was constrained by new limiting data points from the base of overwash deposits associated with the cheniers. These findings have implications for Mississippi River sediment diversions that are currently being planned to restore portions of this vulnerable coast. Only if such diversions are located in the western portion of the Mississippi Delta plain could they potentially contribute to sustaining the CP shoreline. Our findings highlight the importance of a better understanding of mud-dominated shorelines that are often associated with major deltas, in light of the enormous investments in coastal management and restoration that will likely be made around the globe, now and especially later during this century.

Hijma, Marc P.↗
DOE OSTI2023

3. Motion Platforms and Kinematic Arrangements

Within a machine, mechanisms and motion are organized in what is known as a “kinematic arrangement,” which helps classify machines based on how they move. The most common kinematic arrangements for additive manufacturing systems are Cartesian, followed by delta, and then six-degrees-of-freedom robotic arms. However, there are a multitude of less common systems, such as the SCARA, polar robots, cable driven parallel robots, mobile platforms, and multi-agent systems. This chapter surveys these various kinematic arrangements to give a broad understanding of the mechanisms underlying motion within additive manufacturing systems. Understanding these mechanisms and their resulting motion provides a framework for discussing path planning for all scales and families of additive manufacturing.

Wang, Peter↗
DOE OSTI2021

Communication-Avoiding and Memory-Constrained Sparse Matrix-Matrix Multiplication at Extreme Scale

Sparse matrix-matrix multiplication (SpGEMM) is a widely used kernel in various graph, scientific computing and machine learning algorithms. In this paper, we consider SpGEMMs performed on hundreds of thousands of processors generating trillions of nonzeros in the output matrix. Distributed SpGEMM at this extreme scale faces two key challenges: (1) high communication cost and (2) inadequate memory to generate the output. Furthermore, we address these challenges with an integrated communication-avoiding and memory-constrained SpGEMM algorithm that scales to 262,144 cores (more than 1 million hardware threads) and can multiply sparse matrices of any size as long as inputs and a fraction of output fit in the aggregated memory. As we go from 16,384 cores to 262,144 cores on a Cray XC40 supercomputer, the new SpGEMM algorithm runs 10x faster when multiplying large-scale protein-similarity matrices.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Uncovering grain and subgrain microstructure at the scale of additive manufacturing melt tracks with a scalable cellular automaton solidification model

Metal additive manufacturing, characterized by rapid solidification, yields refined grains with a distinctive cellular subgrain microstructure that plays a pivotal role in determining material properties. Due to the significant computational expense demanded to simulate the required physics with submicron spatial resolution, their numerical simulations have been limited to proof-of-concept studies to either 2D or small subregions of a melt pool. In this study, an open-source, scalable, solidification code, muMatScale, based on the cellular automaton method, has been developed to predict the grain and the underlying subgrain microstructure over an entire melt pool. The model incorporates flexible parallelization schemes, utilizing MPI and OpenMP GPU Offloading, in addition to appropriate multi-physics specific to non-equilibrium rapid solidification in AM. The impact of nucleation parameters on grain microstructures was investigated with a focus on grain size variations and morphology transitions. With selected nucleation parameters, the simulation predicted the grain size, subgrain morphology, crystallographic orientation, and microsegregation aligned with experimental measurements. The model demonstrates that epitaxial grain growth is a dominant factor at the melt pool boundary, influencing grain size variation under different grain sizes in the build plate while maintaining consistent primary dendrite arm spacing under identical thermal conditions. Here, the highly efficient numerical model enables large-scale simulations with a spatial resolution of 100 nm or less, unveiling unprecedented insights into thermal and solutal diffusion driven grain growth, and the subgrains with microsegregation within grains in 3D across scales. muMatScale will enable the linking of submicron length-scale microstructure to part-level material behavior by investigating fundamental solidification problems at the intercellular scale in many-track and many-layer builds.

36 MATERIALS SCIENCE↗
DOE OSTI2021

PUMIPic: A mesh-based approach to unstructured mesh Particle-In-Cell on GPUs

Unstructured mesh particle-in-cell, PIC, simulations executing on the current and next generation of massively parallel systems require new methods for both the mesh and particles to achieve performance and scalability on GPUs. The traditional approach to implementing PIC simulations defines data structures and algorithms in terms of particles with a full copy of the unstructured mesh on every process. To effectively scale the unstructured mesh and particles, mesh-based PIC uses the unstructured mesh as the predominant data structure with the particles stored in terms of the mesh entities. Here, this paper details the PUMIPic library, a framework for developing efficient and performance-portable mesh-based PIC simulations on GPU systems. A pseudo physics simulation based on a five-dimensional gyro-kinetic code for modeling plasma physics is used to examine the performance of PUMIPic. Scaling studies of the unstructured mesh partition and number of particles are performed up to 4096 nodes of the Summit system at Oak Ridge National Laboratory. The studies show that mesh-based PIC can utilize a partitioned mesh and maintain scaling up to system limitations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Nebo: An efficient, parallel, and portable domain-specific language for numerically solving partial differential equations

This study presents Nebo, a declarative domain-specific language embedded in C++ for discretizing partial differential equations for transport phenomena on multiple architectures. Application programmers use Nebo to write code that appears sequential but can be run in parallel, without editing the code. Currently Nebo supports single-thread execution, multi-thread execution, and many-core (GPU-based) execution. With single-thread execution, Nebo performs on par with code written by domain experts. With multi-thread execution, Nebo can linearly scale (with roughly 90% efficiency) up to 12 cores, compared to its single-thread execution. Moreover, Nebo’s many-core execution can be over 140x faster than its single-thread execution.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Electric field directed formation of aligned conjugated polymer fibers

Alternating current (AC) electric fields effectively align poly (3-alkylthiophene) (P3AT) fibers during a one-dimensional crystallization process. Structural, mechanical and electrical properties have been probed using microscopy, small angle neutron scattering (SANS), atomic force microscopy (AFM), x-ray diffraction (XRD), rheology, UV-vis spectroscopy, and dielectric spectroscopy. Optimum frequency and amplitudes were identified for specific P3AT concentrations and for variable solvent quality. Optical microscopy along with SANS and XRD demonstrate alignment persists over both micrometer and nanometer length scales. Small amplitude oscillatory shear rheology also showed that the shear modulus increased for aligned fibers. The structural changes were correlated to improvements in electric conductivity as probed by dielectric spectroscopy. XRD experiments performed with variable sample orientations also showed that the P3HT stacking direction was aligned parallel to the direction of the fiber axis. Electric field alignment was also possible for other alkyl-thiophene polymers and for polymers with simple backbone repeat units.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2024

Pretraining Billion-Scale Geospatial Foundational Models on Frontier

As AI workloads increase in scope, generalization capability becomes challenging for small task-specific models and their demand for large amounts of labeled training samples increases. On the contrary, Foundation Models (FMs) are trained with internet-scale unlabeled data via self-supervised learning and have been shown to adapt to various tasks with minimal fine-tuning. Although large FMs have demonstrated significant impact in natural language processing and computer vision, efforts toward FMs for geospatial applications have been restricted to smaller size models, as pretraining larger models requires very large computing resources equipped with state-of-the-art hardware accelerators. Current satellite constellations collect 100+TBs of data a day, resulting in images that are billions of pixels and multimodal in nature. Such geospatial data poses unique challenges opening up new opportunities to develop FMs. We investigate billion scale FMs and HPC training profiles for geospatial applications by pretraining on publicly available data. We studied from end-to-end the performance and impact in the solution by scaling the model size. Our larger 3B parameter size model achieves up to 30% improvement in top1 scene classification accuracy when comparing a 100M parameter model. Moreover, we detail performance experiments on the Frontier supercomputer, America's first exascale system, where we study different model and data parallel approaches using PyTorch's Fully Sharded Data Parallel library. Specifically, we study variants of the Vision Transformer architecture (ViT), conducting performance analysis for ViT models with size up to 15B parameters. By discussing throughput and performance bottlenecks under different parallelism configurations, we offer insights on how to leverage such leadership-class HPC resources when developing large models for geospatial imagery applications.

Tsaris, Aristeidis (aris)↗
DOE OSTI2022

Image Gradient Decomposition for Parallel and Memory-Efficient Ptychographic Reconstruction

Ptychography is a popular microscopic imaging modality for many scientific discoveries and sets the record for highest image resolution. Unfortunately, the high image resolution for ptychographic reconstruction requires significant amount of memory and computations, forcing many applications to compromise their image resolution in exchange for a smaller memory footprint and a shorter reconstruction time. In this paper, we propose a novel image gradient decomposition method that significantly reduces the memory footprint for ptychographic reconstruction by tessellating image gradients and diffraction measurements into tiles. In addition, we propose a parallel image gradient decomposition method that enables asynchronous point-to-point communications and parallel pipelining with minimal overhead on a large number of GPUs. Our experiments on a Titanate material dataset (PbTiO3) with 16632 probe locations show that our Gradient Decomposition algorithm reduces memory footprint by 51 times. In addition, it achieves time-to-solution within 2.2 minutes by scaling to 4158 GPUs with a super-linear strong scaling efficiency at 364% compared to runtimes at 6 GPUs. This performance is 2.7 times more memory efficient, 9 times more scalable and 86 times faster than the state-of-the-art algorithm.

Wang, Xiao↗
DOE OSTI2017

Multistep inversion workflow for 3D long-offset damped elastic waves in the Fourier domain

We present a new workflow for imaging damped three-dimensional elastic wavefields in the Fourier domain. The workflow employs a multiscale imaging approach, in which offset lengths are laddered, where frequency content and damping of the data are changed cyclically. Thus, the inversion process is launched using short-offset and low-frequency data to recover the long spatial wavelength of the image at a shallow depth. Increasing frequency and offset length leads to the recovery of the fine-scale features of the model at greater depths. For the fixed offset, we employ (in the imaging process) a few discrete frequencies with a set of Laplace damping parameters. The forward problem is solved with a finite-difference frequency-domain method based on a massively parallel iterative solver. The inversion code is based upon the solution of a least squares optimisation problem and is solved using a nonlinear gradient method. It is fully parallelised for distributed memory computational platforms. Our full-waveform inversion workflow is applied to the 3D Marmousi-2 and SEG/EAGE Salt models with long-offset data. The maximum inverted frequencies are 6 Hz for the Marmousi model and 2 Hz for the SEG/EAGE Salt model. The detailed structures are imaged successfully up to the depth approximately equal to one-third of the maximum offset length at a resolution consistent with the inverted frequencies.

3D full waveform inversion↗
DOE OSTI2015

Fabrication of nanoporous membranes for tuning microbial interactions and biochemical reactions

Here we describe how new strategies for combining conventional photo- and soft- lithographic techniques with high-resolution patterning and etching strategies are needed in order to produce multi-scale fluidic platforms that address the full range of functional scales seen in complex biological and chemical systems. The smallest resolution required for an application often dictates the fabrication method used. Micromachining and micro-powder blasting yield higher throughput, but lack the resolution needed to fully address biological and chemical systems at the cellular and molecular scales. In contrast, techniques such as electron beam lithography or nanoimprinting allow nanoscale resolution, but are traditionally considered costly and slow. Other techniques such as photolithography or soft lithography have characteristics between these extremes. Combining these techniques to fabricate multi-scale or hybrid fluidics allows fundamental biological and chemical questions can be answered. In this study, a combination of photolithography and electron beam lithography are used to produce two multi-scale fluidic devices that incorporate porous membranes into complex fluidic networks to control the flow of energy, information, and materials in chemical form. In the first device, materials and energy were used to support chemical reactions. A nanoporous membrane fabricated with e-beam lithography separates two parallel, serpentine channels. Photolithography was used to write microfluidic channels around the membrane. The pores were written at 150nm and reduced in size with silicon dioxide deposition from plasma enhanced chemical vapor deposition (PECVD) and atomic layer deposition (ALD). Using this method, the molecular weight cutoff (MWCO) of the membrane can be adapted to the system of interest. In the second approach, photolithography was used to fabricate 200nm thin pores. The pores confined microbes and allowed energy replenishment from a media perfusion channel. The same device can be used for study of intercellular communication via the secretion and uptake of signal molecules. Pore size was tested with 750nm fluorescent polystyrene beads and fluorescein dye. The 200nm PDMS pores were shown to be robust enough to hold 750nm beads while under pressure, but allow fluorescein to diffuse across the barrier. Further testing showed that extended culture of bacteria within the chambers was possible. Finally, these two examples show how lithographically defined porous membranes can be adapted to two unique situations and used to tune the flow of chemical energy, materials, and information within a microfluidic network.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Scalable Preconditioners for Structure Preserving Discretizations of Maxwell Equations in First Order Form

Here, we report multiple physical time-scales can arise in electromagnetic simulations when dissipative effects are introduced through boundary conditions, when currents follow external time-scales, and when material parameters vary spatially. In such scenarios, the time-scales of interest may be much slower than the fastest time-scales supported by the Maxwell equations, therefore making implicit time integration an efficient approach. The use of implicit temporal discretizations results in linear systems in which fast time-scales, which severely constrain the stability of an explicit method, can manifest as so-called stiff modes. This study proposes a new block preconditioner for structure preserving (also termed physics compatible) discretizations of the Maxwell equations in first order form. The intent of the preconditioner is to enable the efficient solution of multiple-time-scale Maxwell type systems. An additional benefit of the developed preconditioner is that it requires only a traditional multigrid method for its subsolves and compares well against alternative approaches that rely on specialized edge-based multigrid routines that may not be readily available. Lastly, results demonstrate parallel scalability at large electromagnetic wave CFL numbers on a variety of test problems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Performance Evaluation of Heterogeneous GPU Programming Frameworks for Hemodynamic Simulations

Preparing for the deployment of large scientific and engineering codes on upcoming exascale systems with GPU-dense nodes is made challenging by the unprecedented diversity of device architectures and heterogeneous programming models. In this work, we evaluate the process of porting a massively parallel, fluid dynamics code written in CUDA to SYCL, HIP, and Kokkos with a range of backends, using a combination of automated tools and manual tuning. We use a proxy application along with a custom performance model to inform the results and identify additional optimization strategies. At scale performance of the programming model implementations are evaluated on pre-production GPU node architectures for Frontier and Aurora, as well as on current NVIDIA device-based systems Summit and Polaris. Real-world workloads representing 3D blood flow calculations in complex vasculature are assessed. Our analysis highlights critical trade-offs between code performance, portability, and development time.

Martin, Aristotle↗
DOE OSTI2016

Next Generation Protein Interactomes for Plant Systems Biology and Biomass Feedstock Research

Biofuel crop cultivation is a necessary step in heading towards a sustainable future, making their genomic studies a priority. While technology platforms that currently exist for studying non-model crop species, like switch-grass or sorghum, have yielded large quantities of genomic and expression data, still a large gap exists between molecular mechanism and phenotype. The aspect of molecular activity at the level of protein-protein interactions has recently begun to bridge this gap, providing a more global perspective. Interactome analysis has defined more specific functional roles of proteins based on their interaction partners, neighborhoods, and other network features, making it possible to distinguish unique modules of immune response to different plant pathogens(Jiang, Dong, and Zhang 2016). As we work towards cultivating heartier biofuel crops, interactome data will lead to uncovering crop-specific defense and development networks. However, the collection of protein interaction data has been limited to expensive, time-consuming, hard-to-scale assays that mostly require cloned ORF collections. For these reasons, we have successfully developed a highly scalable, economical, and sensitive yeast two-hybrid assay, ProCREate, that can be universally applied to generate proteome-wide primary interactome data. ProCREate enables en masse pooling and massively paralleled sequencing for the identification of interacting proteins by exploiting Cre-lox recombination. ProCREate can be used to screen ORF/cDNA libraries from feedstock plant tissues. The interactome data generated will yield deeper insight into many molecular processes and pathways that can be used to guide improvement of feedstock productivity and sustainability.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Productive Programming of Distributed Systems with the SHAD C++ Library

High-performance computing (HPC) is often perceived as a matter of making large-scale systems (e.g., clusters) run as fast as possible, regardless the required programming effort. However, the idea of "bringing HPC to the masses" has recently emerged. Inspired by this vision, we have designed SHAD, the Scalable High-performance Algorithms and Data-structures library. SHAD is open source software, written in C++, for C++ developers. Unlike other HPC libraries for distributed systems, which rely on SPMD models, SHAD adopts a shared-memory programming abstraction, to make C++ programmers feel at home. Underneath, SHAD manages tasking and data-movements, moving the computation where data resides and taking advantage of asynchrony to tolerate network latency. At the bottom of his stack, SHAD can interface with multiple runtime systems: this not only improves developer’s productivity, by hiding the complexity of such software and of the underlying hardware, but also greatly enhance code portability. Thanks to its abstraction layers, SHAD can indeed target different systems, ranging from laptops to HPC clusters, without any need for modifying the user-level code. We have prototyped and open-sourced the implementation of (a subset of) the C++ standard library (STL) targeting multi-node HPC clusters. Our work allows plain STL-based C++ code to scale on HPC systems, with no need for rewriting the code to exploit the complex hardware. SHAD is available under Apache v2 License at https://github.com/pnnl/SHAD. In this paper we overview the design of the SHAD library, depicting its main components: runtime systems abstractions for tasking; parallel and distributed data-structures; STL-compliant interfaces and algorithms.

Castellana, Vito G.↗