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At least 289 records · Page 16

Race conditions and data partitioning: risks posed by common errors to reproducible parallel simulations

When parallel algorithms for simulation were introduced in the 1970s, their development and use interested only experts in parallel computation. This circumstance changed as multi-core processors became commonplace, putting a parallel computer into the hands of every modeler. A natural outcome is growing interest in parallel simulation among persons not intimately familiar with parallel computing. At the same time, parallel simulation tools continue to be developed with the implicit assumption that the modeler is knowledgeable about parallel programming. The unintended consequence is a rapidly growing number of users of parallel simulation tools that are unlikely to recognize when the interaction of race conditions, partitioning strategies, and simultaneous action in their simulation models make results non-reproducible, thereby calling into question the validity of conclusions drawn from the simulation data. Here, we illustrate the potential dangers of exposing parallel algorithms to users who are not experts in parallel computation with example models constructed using existing parallel simulation tools. By doing so, we hope to refocus tool developers on usability, even if this new focus incurs loss of some performance.

97 MATHEMATICS AND COMPUTING↗

Tracking Radioactive Isotopes in HVAC and Application for Hot Cell Analyses - 20155

In recent years, the surge in the number of isotope production facilities under design has increased the need to analyze isotope migration in facility Heating, Ventilation, and Air Conditioning (HVAC) during normal operations and accident scenarios. These facilities are used to produce isotopes for medical, security, and industrial applications and as such are subject to license and regulatory requirements 10CFR20, 10CFR30, 10CFR50, and 10CFR70. GOTHIC, a general-purpose thermal-hydraulics software package, includes the ability to model isotopic tracers, radioactive decay and isotope migration as well as HEPA and charcoal filters for isotope retention. A GOTHIC model was developed by Zachry Nuclear Engineering (ZNE) to examine the effect of negative room pressure, HEPA filtration, and HVAC fluctuations on radiation areas, hot cells and gloveboxes. Radioactive tracers were used to simulate the concentration of spills within contaminated areas, track the migration of isotopes of interest, and determine the isotopic retention and buildup on facility HEPA filters. A variety of isotopes with concern to dose (e.g., Kr-85, Sr-90, I-131, etc.), including their decay and progeny, are included in the analysis. Negative pressures are maintained in the regions of interest by a representative central HVAC system equipped with a volumetric fan that exhausts to the environment after a series of isolation valves and HEPA filters. GOTHIC is an industry trusted tool for providing engineering solutions for a variety of applications, including fission product tracking, aerosol and particulate transport and ventilation assessments. The software provides an integrated analysis environment that includes a graphical user interface (GUI) for constructing analysis models, a numerical solver that includes parallel processing capabilities and a post-processor for evaluating simulation results. It solves the conservation equations for mass, momentum and energy for multicomponent, multi-phase flow in lumped parameter and multi-dimensional geometries (1, 2, or full 3D), including the effects of turbulence, diffusion and buoyancy. It has been developed and maintained under a Quality Assurance program in compliance with the requirements of 10CFR50 Appendix B and applicable portions of ASME NQA-1 since 1995. GOTHIC has been used for assessing both forced and natural convection conditions for a wide range of applications, including: - Tracking concentration of hazardous gases and chemicals for habitability and safety assessments - Determining ventilation and filtration requirements and optimizing location and arrangement of these systems - Room heat-up, including diverse and Flexible coping strategies for Extended Loss of AC Power (FLEX/ELAP) - Equipment Qualification (EQ) A distinctive feature of GOTHIC is the ability to track many different fields/substances in a simulation, including user defined tracer elements, in the liquid, vapor and droplet fields as well as surfaces and filters. This capability allows GOTHIC to model fission product transport and release or the removal of particulates or harmful toxins from exhaust gases using a spray scrubber or other types of filtration systems. GOTHIC also includes models for engineered equipment, such as fans, filters, charcoal filters, dryers/demisters, dampers, etc. The aerosols and other filtered material are removed or accumulated in these components. The range of aerosol and radiological applications that GOTHIC has been used for includes: - Source Term: Primary Coolant (Equilibrium) Activity; Non-Water Coolant Source/Leakage. - Conditions for Iodine Re-evolution: Sump/Suppression Pool Conditions and pH; - RWST Conditions and pH. - Isotope Removal Mechanisms: Containment Sprayed and Unsprayed Region Mixing; Charcoal Filter Heating due to Iodine decay. - Radionuclide Transport and Decay: Post-LOCA Release in containment; Transport between connected Compartments and vent systems; Groundwater transport of radionuclides. - Non-Newtonian Fluid modeling for sludge, waste tanks, etc. ADAMS ML071581053 (titled 'Best Practice Guidelines for the use of CFD in Nuclear Reactor Safety Applications') poses guidelines for applying single phase CFD codes in nuclear reactor safety problems and GOTHIC is listed as a 'tool for 3D flows' and 'dispersal and deposition of radionuclides.' The Nuclear Quality Assurance (NQA) pedigree of GOTHIC is an important aspect for applications in the nuclear industry. The fundamental tracer models (convective transport, molecular and turbulent diffusion, removal mechanisms, etc.) have been verified using analytical solutions and validated against applicable separate effects tests. Also, GOTHIC has been benchmarked to many integrated effects tests, including Phebus FP (Fission Product). GOTHIC gives good agreement for the buildup and decay of fission products in Phebus Test 3. The model developed by ZNE demonstrates GOTHIC's applicability and acceptability for use in analyzing the migration and retention of radioactive isotopes and their progeny in normal operation and accident scenario analyses for isotope production facilities, hot cells, and gloveboxes. The tracer activities calculated by GOTHIC can then be used in downstream radiation transport and shielding codes like RADTRAD-NAI{sup C}, MCNP{sup R}, and MicroShield{sup R} to determine on-site and of-site doses. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

SU-E-I-04: A Mammography Phantom to Measure Mean Glandular Dose and Image Quality

Purpose: To evaluate mean glandular dose (MGD) and image quality in a selection of mammography systems using a novel phantom based on thermoluminescent dosemeters and the ACR wax insert. Methods: The phantom consists of two acrylic, 19 cm diameter, 4.5 cm thick, semicircular modules, used in sequence. The image quality module contains the ACR insert and is used to obtain a quality control image under automatic exposure conditions. The dosimetric module carries 15 TLD-100 chips, some under Al foils, to determine air kerma and half-value-layer. TL readings take place at our laboratory under controlled conditions. Calibration was performed using an ionization chamber and a Senographe 2000D unit for a variety of beam qualities, from 24 to 40 kV, Mo and Rh anodes and filters. Phantom MGD values agree, on the average, within 3% with ionization chamber data, and their precision is better than 10% (k=1). Results: MGD and image quality have been evaluated in a selection of mammography units currently used in Mexican health services. The sample includes analogic (screen/film), flexible digital (CR), and full-field digital image receptors. The highest MDG are associated to the CR technology. The most common image quality failure is due to artifacts (dust, intensifying screen scratches, and processor marks for film/screen, laser reader defects for CR). Conclusion: The developed phantom permits the MGD measurement without the need of a calibrated ionization chamber at the mammography site and can be used by a technician without the presence of a medical physicist. The results indicate the urgent need to establish quality control programs for mammography.

07 ISOTOPE AND RADIATION SOURCES↗

Mechanical and biochemical recovery of landfill waste in an underserved community

Historically in the United States, waste collected for recycling has been sold and shipped to processors in China. In 2013 and 2018, China introduced the Green Fence and National Sword policies which restricts the import of contaminated materials and banned the import of many recyclables. The cost of recycling in the United States has increased following these policy changes, which has led to many communities reducing their recycling programs or halting them altogether. Rural and underserved communities that don’t have resources to afford sophisticated recycling programs have been heavily impacted. Previous work at INL demonstrated that MSW is a potentially viable feedstock for both biochemical and thermochemical conversion. The goal of this project is to assess preprocessing tools that can produce consistent feedstocks that meet conversion specifications, remove problematic contaminants, and reduce the amount of waste that is landfilled. Municipal solid waste was collected from an underserved community in southeast Idaho, contaminants were characterized, and mechanically separated into two discrete fractions. The unit operations identified during mechanical separation trials will be mobilized to on-site with a goal of 50% recovery of paper and plastic waste.

09 - BIOMASS FUELS↗

Creating a Parallel Version of VisIt for Microsoft Windows

VisIt is a popular, free interactive parallel visualization and analysis tool for scientific data. Users can quickly generate visualizations from their data, animate them through time, manipulate them, and save the resulting images or movies for presentations. VisIt was designed from the ground up to work on many scales of computers from modest desktops up to massively parallel clusters. VisIt is comprised of a set of cooperating programs. All programs can be run locally or in client/server mode in which some run locally and some run remotely on compute clusters. The VisIt program most able to harness today's computing power is the VisIt compute engine. The compute engine is responsible for reading simulation data from disk, processing it, and sending results or images back to the VisIt viewer program. In a parallel environment, the compute engine runs several processes, coordinating using the Message Passing Interface (MPI) library. Each MPI process reads some subset of the scientific data and filters the data in various ways to create useful visualizations. By using MPI, VisIt has been able to scale well into the thousands of processors on large computers such as dawn and graph at LLNL. The advent of multicore CPU's has made parallelism the 'new' way to achieve increasing performance. With today's computers having at least 2 cores and in many cases up to 8 and beyond, it is more important than ever to deploy parallel software that can use that computing power not only on clusters but also on the desktop. We have created a parallel version of VisIt for Windows that uses Microsoft's MPI implementation (MSMPI) to process data in parallel on the Windows desktop as well as on a Windows HPC cluster running Microsoft Windows Server 2008. Initial desktop parallel support for Windows was deployed in VisIt 2.4.0. Windows HPC cluster support has been completed and will appear in the VisIt 2.5.0 release. We plan to continue supporting parallel VisIt on Windows so our users will be able to take full advantage of their multicore resources.

97 MATHEMATICS AND COMPUTING↗

MPACT FY2011 Advanced Time-Correlated Measurement Research at INL

Simulations and experiments have been carried out to investigate advanced time-correlated measurement methods for characterizing and assaying nuclear material for safeguarding the nuclear fuel cycle. These activities are part of a project studying advanced instrumentation techniques in support of the U.S. Department of Energy's Fuel Cycle Research and Development program and its Materials Protection, Accounting, and Control Technologies (MPACT) program. For fiscal year 2011 work focused on examining the practical experimental aspects of using a time-tagged, associated-particle electronic neutron generator for interrogating low-enrichment uranium in combination with steady-state interrogation using a moderated 241Am-Li neutron source. Simulation work for the project involved the use of the MCNP-PoliMi Monte Carlo simulation tool to determine the relative strength and the time-of-flight energy spectra of different sample materials under irradiation. Work also took place to develop a post-processor parser code to extract comparable data from the MCNP5&6 codes. Experiments took place using a commercial deuterium-tritium associated-particle electronic neutron generator to irradiate a number of uranium-bearing material samples. Time-correlated measurements of neutron and photon signatures of these measurements were made using five liquid scintillator detectors in a novel array, using high-speed waveform digitizers for data collection. This report summarizes the experiments that took place in FY2011, presents preliminary analyses that have been carried out to date for a subpart of these experiments, and describes future activities planned in this area. The report also describes support Idaho National Laboratory gave to Oak Ridge National Laboratory in 2011 to facilitate 2-dimensional imagery of mixed-oxide fuel pins for safeguards applications as a part of the MPACT program.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Performance and scalability evaluation of "Big Memory" on Blue Gene Linux.

We address memory performance issues observed in Blue Gene Linux and discuss the design and implementation of 'Big Memory' - an alternative, transparent memory space introduced to eliminate the memory performance issues. We evaluate the performance of Big Memory using custom memory benchmarks, NAS Parallel Benchmarks, and the Parallel Ocean Program, at a scale of up to 4,096 nodes. We find that Big Memory successfully resolves the performance issues normally encountered in Blue Gene Linux. For the ocean simulation program, we even find that Linux with Big Memory provides better scalability than does the lightweight compute node kernel designed solely for high-performance applications. Originally intended exclusively for compute node tasks, our new memory subsystem dramatically improves the performance of certain I/O node applications as well. We demonstrate this performance using the central processor of the LOw Frequency ARray radio telescope as an example.

59 BASIC BIOLOGICAL SCIENCES↗

Trinity Supercomputer Now Fully Operational

Now one of the fastest supercomputers in the United States, the Trinity Supercomputer Phase II project was completed during the summer of 2017, and the computer became fully operational during an unclassified “open science” run. The computer has now transitioned to classified mode. The Trinity supercomputer is designed to provide increased computational capability for the NNSA Nuclear Security Enterprise in support of increasing geometric and physics fidelities in nuclear weapons simulation codes, while maintaining expectations for total time to solution. The capabilities of Trinity are required for supporting the NNSA Stockpile Stewardship program’s certification and assessments to ensure that the nation’s nuclear stockpile is safe, secure and effective. With an expected operational lifetime through 2020, Trinity is an approximately 41.5 petaflop (41.5 million billion calculations per second, peak performance) supercomputer based on the Cray XC40 architecture. It consists of 19,420 compute nodes utilizing two processor architectures, Intel Xeon Haswell and Intel Xeon Phi Knights Landing. It is a water-cooled system with a power requirement of about 10 megawatts. The Trinity project is managed and operated by Los Alamos National Laboratory and Sandia National Laboratories under the Alliance for Computing at Extreme Scale (ACES) partnership. The system is located at the Nicholas Metropolis Center for Modeling and Simulation at Los Alamos and covers approximately 5,200 square feet of floor space.

97 MATHEMATICS AND COMPUTING↗

Parallel Monte Carlo Methods for Heterogeneous Hardware Computer Systems Using GPUs and Coprocessors: Recent Development of ARCHER Code - Paper 54

Traditional methods of accelerating Monte Carlo (MC) calculations typically use CPUs as the computing unit. The parallelism is based upon multithreading on a multi-core processor, and message passing interface (MPI) across many processors and nodes. In recent years, the hardware accelerators have been introduced by the high performance computing industry as an alternative approach to achieve massive parallelism. Hardware accelerators have the advantage of high Floating-point Operations Per Second (FLOPS) and high energy efficiency. Examples include graphics processing units (GPUs) and coprocessors. Compute-intensive programs can be off-loaded to them to be concurrently executed by hundreds or thousands of active threads. Existing production MC codes, however, cannot be directly compiled or executed on the new platforms. It is therefore necessary to rewrite or redevelop the code using the hardware accelerator specific programming models and APIs. Several studies have been conducted on using GPUs to accelerate MC calculations in reactor analysis and medical physics. In this paper, we present the recent progress at Rensselaer Polytechnic Institute (RPI) in developing a new parallel MC code called ARCHER (Accelerated Radiation-transport Computations in Heterogeneous Environments) for coupled photon-electron transport simulations. The code is designed as a test bed to evaluate the efficacy of heterogeneous computing systems for low-cost MC-based radiation dosimetric calculations. The code has three variants corresponding to three parallel hardware platforms: ARCHER-CPU (multi-core CPU), ARCHER-GPU (Nvidia GPU) and ARCHER-COP (Intel Xeon Phi coprocessor). The code has been used for several applications, including CT imaging dosimetry, radiotherapy dosimetry and radiation shielding design. (authors)

61 RADIATION PROTECTION AND DOSIMETRY↗

The Institute for Sustained Performance, Energy, and Resilience Final Project Report

Over the course of the five years of the Scientific Discovery through Advanced Computation (SciDAC-3) program, computational scientists working on behalf of the Department of Energy's Office of Science (DOE SC) exploited a new generation of petascale computing resources to make previously inaccessible discoveries in a broad range of disciplines including physics, chemistry, and materials science. The computing systems underpinning this work increased in performance potential from tens to hundreds of PFlop/s, but in the process evolving significantly from architectures in 2011, when SciDAC-3 began. Although Moore's law continues unabated, the end of Dennard scaling has necessitated a fundamental shift in computer architecture focused on power efficiency. To that end, processors are increasingly varied as they strive to satisfy performance, productivity, reliability, and energy efficiency in the face of divergent computational requirements. The diversity among these machines presents a number of challenges to merely porting today's scientific applications, much less achieving good performance. Therefore, at the beginning of SciDAC-3, USC and its collaborators anticipated that both vastly increased scale (e.g., more chips, more cores per chip, wider SIMD) and heterogeneity would exacerbate performance optimization challenges while simultaneously promoting the issues of energy and heterogeneity will exacerbate performance optimization challenges while simultaneously promoting the issues of energy consumption and resilience to the forefront. To ensure that DOE's computational scientists could successfully exploit emerging high performance computing (HPC) systems, DOE SC’s Advanced Scientific Computing Research Program (ASCR) funded the SciDAC-3 Institute for Sustained Performance, Energy, and Resilience (SUPER). Led by USC, this was a broadly based project with expertise in compilers and system tools, performance engineering, energy management, and resilience. SUPER followed the successful model developed in the previous SciDAC-2 Performance Engineering Research Institute (PERI) of leveraging the research investments DOE and others have made and integrating the results to create new capabilities beyond the reach of any one group. To accomplish this, SUPER was organized into multi-institution teams conducting the research activities in performance portability, energy efficiency, exascale resilience, and overall optimization. SUPER researchers also collaborated with other SciDAC-3 institutes, 13 of the 19 Scientific Computation Application Partnerships (SAP), as well as the broader DOE computational sciences community. These collaborations both focused our research on the real challenges facing petascale scientific computing as well as ensured the broad and immediate impact of the results of our research.

97 MATHEMATICS AND COMPUTING↗

Performance assessment modernization at WIPP - 15077

To aid in WIPP PA calculations, the US DOE has undertaken a broad modernization effort that includes: 1) updating the hardware and operating system used; 2) moving the current PA (performance assessment) codes to the new system; and 3) adding a database to store results essential for the analysis of assessments; 4) integrating run-control scripts with a web site to facilitate monitoring of performance assessment calculations; and 5) adding new capabilities via implementation of the PFLOTRAN code to replace multiple codes currently in use. The majority of codes were migrated from an Open VMS/Alpha processor system to a Unix/Intel processor system. Most codes were upgraded to use the dynamic allocation features of Fortran 95 and double precision variables. A few codes were migrated from Linux/Intel systems to the Unix/Intel systems and these code required nearly no changes to the source code. All of the migrated codes were re-qualified under Sandia's WIPP QA program. The implementation of some of the conceptual models using PFLOTRAN is being driven by the expectation that changes in the configuration of the repository will require a 3-dimensional representation of the mined areas. Symmetry in the current configuration of the repository made a 2-D representation adequate. PFLOTRAN is an open-source, state-of-the-art massively parallel subsurface flow and reactive transport code. A version of this code is being developed specifically for WIPP PA in order to maintain the capabilities of the current flow and transport codes, as well as add the capabilities of a parallel code that will treat additional processes, including: 1) miscible multi-phase flow; and 2) heat transfer. PFLOTRAN will replace the two codes (i.e. BRAGFLO and NUTS) currently used for flow and transport calculations, simplifying the PA code structure and speeding up calculations by simultaneously solving for flow and transport with a single code. To ensure that PFLOTRAN reproduces the results of the current code suite, existing test cases have been used for verification purposes. Additional test cases have been developed to establish the new capabilities for WIPP PA. The result of the modernization effort will be a state-of-the-art subsurface flow and transport capability that will serve WIPP PA into the future. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Parallelizing AT with MatlabMPI

The Accelerator Toolbox (AT) is a high-level collection of tools and scripts specifically oriented toward solving problems dealing with computational accelerator physics. It is integrated into the MATLAB environment, which provides an accessible, intuitive interface for accelerator physicists, allowing researchers to focus the majority of their efforts on simulations and calculations, rather than programming and debugging difficulties. Efforts toward parallelization of AT have been put in place to upgrade its performance to modern standards of computing. We utilized the packages MatlabMPI and pMatlab, which were developed by MIT Lincoln Laboratory, to set up a message-passing environment that could be called within MATLAB, which set up the necessary pre-requisites for multithread processing capabilities. On local quad-core CPUs, we were able to demonstrate processor efficiencies of roughly 95% and speed increases of nearly 380%. By exploiting the efficacy of modern-day parallel computing, we were able to demonstrate incredibly efficient speed increments per processor in AT's beam-tracking functions. Extrapolating from prediction, we can expect to reduce week-long computation runtimes to less than 15 minutes. This is a huge performance improvement and has enormous implications for the future computing power of the accelerator physics group at SSRL. However, one of the downfalls of parringpass is its current lack of transparency; the pMatlab and MatlabMPI packages must first be well-understood by the user before the system can be configured to run the scripts. In addition, the instantiation of argument parameters requires internal modification of the source code. Thus, parringpass, cannot be directly run from the MATLAB command line, which detracts from its flexibility and user-friendliness. Future work in AT's parallelization will focus on development of external functions and scripts that can be called from within MATLAB and configured on multiple nodes, while expending minimal communication overhead with the integrated MATLAB library.

43 PARTICLE ACCELERATORS↗

The ATLAS experiment software on ARM

With an increased dataset obtained during the Run 3 of the LHC at CERN and the even larger expected increase of the dataset by more than one order of magnitude for the HL-LHC, the ATLAS experiment is reaching the limits of the current data processing model in terms of traditional CPU resources based on x86_64 architectures and an extensive program for software upgrades towards the HL-LHC has been set up. The ARM architecture is becoming a competitive and energy efficient alternative. Some surveys indicate its increased presence in HPCs and commercial clouds, and some WLCG sites have expressed their interest. Chip makers are also developing their next generation solutions on ARM architectures, sometimes combining ARM and GPU processors in the same chip. Consequently it is important that the ATLAS software embraces the change and is able to successfully exploit this architecture. We report on the successful porting to ARM of the Athena software framework, which is used by ATLAS for both online and offline computing operations. Furthermore we report on the successful validation of simulation workflows running on ARM resources. For this we have set up an ATLAS Grid site using ARM compatible middleware and containers on Amazon Web Services (AWS) ARM resources. The ARM version of Athena is fully integrated in the regular software build system and distributed in the same way as other software releases. In addition, the workflows have been integrated into the HEPscore benchmark suite which is the planned WLCG wide replacement of the HepSpec06 benchmark used for Grid site pledges. In the overall porting process we have used resources on AWS, Google Cloud Platform (GCP) and CERN. A performance comparison of different architectures and resources will be discussed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

The Secret Life of Quarks, Final Report for the University of North Carolina at Chapel Hill

This final report summarizes activities and results at the University of North Carolina as part of the the SciDAC-2 Project The Secret Life of Quarks: National Computational Infrastructure for Lattice Quantum Chromodynamics. The overall objective of the project is to construct the software needed to study quantum chromo- dynamics (QCD), the theory of the strong interactions of subatomic physics, and similar strongly coupled gauge theories anticipated to be of importance in the LHC era. It built upon the successful efforts of the SciDAC-1 project National Computational Infrastructure for Lattice Gauge Theory, in which a QCD Applications Programming Interface (QCD API) was developed that enables lat- tice gauge theorists to make effective use of a wide variety of massively parallel computers. In the SciDAC-2 project, optimized versions of the QCD API were being created for the IBM Blue- Gene/L (BG/L) and BlueGene/P (BG/P), the Cray XT3/XT4 and its successors, and clusters based on multi-core processors and Infiniband communications networks. The QCD API is being used to enhance the performance of the major QCD community codes and to create new applications. Software libraries of physics tools have been expanded to contain sharable building blocks for inclusion in application codes, performance analysis and visualization tools, and software for au- tomation of physics work flow. New software tools were designed for managing the large data sets generated in lattice QCD simulations, and for sharing them through the International Lattice Data Grid consortium. As part of the overall project, researchers at UNC were funded through ASCR to work in three general areas. The main thrust has been performance instrumentation and analysis in support of the SciDAC QCD code base as it evolved and as it moved to new computation platforms. In support of the performance activities, performance data was to be collected in a database for the purpose of broader analysis. Third, the UNC work was done at RENCI (Renaissance Computing Institute), which has extensive expertise and facilities for scientific data visualization, so we acted in an ongoing consulting and support role in that area.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Software Synthesis for High Productivity Exascale Computing

Over the three years of our project, we accomplished three key milestones: We demonstrated how ideas from generative programming and software synthesis can help support the development of bulk-synchronous distributed memory kernels. These ideas are realized in a new language called MSL, a C-like language that combines synthesis features with high level notations for array manipulation and bulk-synchronous parallelism to simplify the semantic analysis required for synthesis. We also demonstrated that these high level notations map easily to low level C code and show that the performance of this generated code matches that of handwritten Fortran. Second, we introduced the idea of solver-aided domain-specific languages (SDSLs), which are an emerging class of computer-aided programming systems. SDSLs ease the construction of programs by automating tasks such as verification, debugging, synthesis, and non-deterministic execution. SDSLs are implemented by translating the DSL program into logical constraints. Next, we developed a symbolic virtual machine called Rosette, which simplifies the construction of such SDSLs and their compilers. We have used Rosette to build SynthCL, a subset of OpenCL that supports synthesis. Third, we developed novel numeric algorithms that move as little data as possible, either between levels of a memory hierarchy or between parallel processors over a network. We achieved progress in three aspects of this problem. First we determined lower bounds on communication. Second, we compared these lower bounds to widely used versions of these algorithms, and noted that these widely used algorithms usually communicate asymptotically more than is necessary. Third, we identified or invented new algorithms for most linear algebra problems that do attain these lower bounds, and demonstrated large speed-ups in theory and practice.

97 MATHEMATICS AND COMPUTING↗

Approximate error conjugation gradient minimization methods

In one embodiment, a method includes selecting a subset of rays from a set of all rays to use in an error calculation for a constrained conjugate gradient minimization problem, calculating an approximate error using the subset of rays, and calculating a minimum in a conjugate gradient direction based on the approximate error. In another embodiment, a system includes a processor for executing logic, logic for selecting a subset of rays from a set of all rays to use in an error calculation for a constrained conjugate gradient minimization problem, logic for calculating an approximate error using the subset of rays, and logic for calculating a minimum in a conjugate gradient direction based on the approximate error. In other embodiments, computer program products, methods, and systems are described capable of using approximate error in constrained conjugate gradient minimization problems.

97 MATHEMATICS AND COMPUTING↗

Portable Data-Parallel Surface Reconstruction on a Uniform Rectilinear Grid

With the increasing heterogeneity and on-node parallelism of high-performance computing hardware, a major challenge is to develop portable and efficient algorithms and software. In this work, we present our implementation of a portable code to perform surface reconstruction using NVIDIA's Thrust library. Surface reconstruction is a technique commonly used in volume tracking methods for simulations of multimaterial flow with interfaces. Here, we have designed a 3D mesh data structure that is easily mapped to the 1D vectors used by Thrust and at the same time is simple to use and uses familiar data structure terminology (such as cells, faces, vertices, and edges). With this new data structure in place, we have implemented a piecewise linear interface reconstruction algorithm in 3 dimensions that effectively exploits the symmetry present in a uniform rectilinear computational cell. Finally, we report performance results, which show that a single implementation of these algorithms can be compiled to multiple backends (specifically, multi-core CPUs, NVIDIA GPUs, and Intel Xeon Phi processors), making efficient use of the available parallelism on each. We also compare performance of our implementation to a legacy FORTRAN implementation in Message Passing Interface (MPI) and show performance parity on single and multi-core CPU and achieved good parallel speed-ups on GPU. In conclusion, our research demonstrates the advantage of performance portability of the underlying data-parallel programming model.

97 MATHEMATICS AND COMPUTING↗

Ground-referenced single-ended signaling connected graphics processing unit multi-chip module

A system of interconnected chips comprising a multi-chip module (MCM) includes a first processor chip, a graphics processing cluster (GPC) chip, and an MCM package configured to include the first processor chip, the GPC chip, and an interconnect circuit. The first processor chip is configured to include a first ground-referenced single-ended signaling interface circuit. A first set of electrical traces fabricated within the MCM package and configured to couple the first single-ended signaling interface circuit to the interconnect circuit. The GPC chip is configured to include a second single-ended signaling interface circuit and to execute shader programs. A second set of electrical traces fabricated within the MCM package and configured to couple the second single-ended signaling interface circuit to the interconnect circuit. In one embodiment, each single-ended signaling interface advantageously implements ground-referenced single-ended signaling.

Dally, William J.↗