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At least 505 records · Page 28

Coarse-Grain Bandwidth Estimation Scheme for Large-Scale Network

A large-scale network that supports a large number of users can have an aggregate data rate of hundreds of Mbps at any time. High-fidelity simulation of a large-scale network might be too complicated and memory-intensive for typical commercial-off-the-shelf (COTS) tools. Unlike a large commercial wide-area-network (WAN) that shares diverse network resources among diverse users and has a complex topology that requires routing mechanism and flow control, the ground communication links of a space network operate under the assumption of a guaranteed dedicated bandwidth allocation between specific sparse endpoints in a star-like topology. This work solved the network design problem of estimating the bandwidths of a ground network architecture option that offer different service classes to meet the latency requirements of different user data types. In this work, a top-down analysis and simulation approach was created to size the bandwidths of a store-and-forward network for a given network topology, a mission traffic scenario, and a set of data types with different latency requirements. These techniques were used to estimate the WAN bandwidths of the ground links for different architecture options of the proposed Integrated Space Communication and Navigation (SCaN) Network. A new analytical approach, called the "leveling scheme," was developed to model the store-and-forward mechanism of the network data flow. The term "leveling" refers to the spreading of data across a longer time horizon without violating the corresponding latency requirement of the data type. Two versions of the leveling scheme were developed: 1. A straightforward version that simply spreads the data of each data type across the time horizon and doesn't take into account the interactions among data types within a pass, or between data types across overlapping passes at a network node, and is inherently sub-optimal. 2. Two-state Markov leveling scheme that takes into account the second order behavior of the store-and-forward mechanism, and the interactions among data types within a pass. The novelty of this approach lies in the modeling of the store-and-forward mechanism of each network node. The term store-and-forward refers to the data traffic regulation technique in which data is sent to an intermediate network node where they are temporarily stored and sent at a later time to the destination node or to another intermediate node. Store-and-forward can be applied to both space-based networks that have intermittent connectivity, and ground-based networks with deterministic connectivity. For groundbased networks, the store-and-forward mechanism is used to regulate the network data flow and link resource utilization such that the user data types can be delivered to their destination nodes without violating their respective latency requirements.

Cheung, Kar-Ming↗

Evolution of the ATLAS event data model for the HL-LHC

The upcoming high-luminosity run of the CERN Large Hadron Collider (HL-LHC) will yield an unprecedented volume of data. In order to process this data, the ATLAS collaboration is evolving its offline software to be able to use heterogeneous resources such as graphical processing units (GPUs) and field-programmable gate arrays (FPGAs). To reduce conversion overheads, the event data model (EDM) should be compatible with the requirements of these resources. While the ATLAS EDM has long allowed representing data as a structure of arrays, further evolution of the EDM can enable more efficient sharing of data between CPU and GPU resources. Some of this work will be summarized here, including extensions to allow controlling how memory for event data is allocated and the implementation of jagged vectors.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Multipurpose Panel Display Device Investigation

A multipurpose panel was developed to provide a flexible control and a LED display panel with easily changeable nomenclature for use in applications where panel space is limited, but where a number of similar subsystems must be controlled, or where basic panel nomenclature and functions must be changed rapidly, as in the case of between mission changes of space shuttle payloads. In the first application, panel area limitations are overcome by time sharing a central control panel among several subsystems. In the latter case, entire control panel changes are effected by simply replacing a memory module, thereby reducing the extent of installation and checkout procedures between missions. Several types of control technologies (other than LED's) which show potential in meeting criteria for overcoming limitations of the panel are assessed.

Sliwa, R.↗

Job Management Requirements for NAS Parallel Systems and Clusters

A job management system is a critical component of a production supercomputing environment, permitting oversubscribed resources to be shared fairly and efficiently. Job management systems that were originally designed for traditional vector supercomputers are not appropriate for the distributed-memory parallel supercomputers that are becoming increasingly important in the high performance computing industry. Newer job management systems offer new functionality but do not solve fundamental problems. We address some of the main issues in resource allocation and job scheduling we have encountered on two parallel computers - a 160-node IBM SP2 and a cluster of 20 high performance workstations located at the Numerical Aerodynamic Simulation facility. We describe the requirements for resource allocation and job management that are necessary to provide a production supercomputing environment on these machines, prioritizing according to difficulty and importance, and advocating a return to fundamental issues.

Saphir, William↗

Crystallographic and general use programs for the XDS Sigma 5 computer

Programs in basic FORTRAN 4 are described, which fall into three catagories: (1) interactive programs to be executed under time sharing (BTM); (2) non interactive programs which are executed in batch processing mode (BPM); and (3) large non interactive programs which require more memory than is available in the normal BPM/BTM operating system and must be run overnight on a special system called XRAY which releases about 45,000 words of memory to the user. Programs in catagories (1) and (2) are stored as FORTRAN source files in the account FSNYDER. Programs in catagory (3) are stored in the XRAY system as load modules. The type of file in account FSNYDER is identified by the first two letters in the name.

Snyder, R. L.↗

Preface to the Special Collection: Recollections in Space Physics

Space Physics is a comparatively young scientific discipline, tightly linked to the era of satellite based investigations and the discoveries that came with it. As such, we as a community are fortunate to have met, been taught and mentored by, and even become friends with, many of those who were around to witness the birth of, and in many cases establish, our field. Each of these "Pioneers" have remarkable stories to tell. These accounts from the dawn of the space age provide a glimpse into that era of scientific discovery and are an important part of our collective history that deserve to be shared and commemorated. These are stories of perseverance, ingenuity, luck, and sometimes failure. We are fortunate to live in an era in which these distinguished scientists are still with us and able to share their experiences.To commemorate the 100th Anniversary of the American Geophysical Union (AGU), we have solicited a special collection of recollection papers to memorialize these experiences. This is not the first such effort to capture these stories. In 1994 (Vol. 99, No. A10, pp. 19,099-19,212) and again in 1996 (Vol. 101, No. A5, pp. 10,477-10,585) JGRSpace Physics published special sections entitled, "Pioneers of Space Physics," in celebration of AGU's 75th anniversary. Later, in 1997, Gilmore and Spreiter (1997) added a set of recollection papers on the discovery of the magnetosphere. Together, these papers containing personal accounts from the pioneers of the space age covered the period of roughly 1958-1967.It is our great honor to present retrospective papers from several of our distinguished colleagues who contributed significantly to the explosion in understanding of space physics and aeronomy that occurred from roughly 1967-1980. We chose to start at the end of the previous set of recollections and cover the decade of the 1970s, during which our field greatly expanded. It is also a time in which the second generation of space scientists entered the field and made foundational discoveries that continue to define our discipline.As with the previous papers, we asked the authors to "recount some of the events leading to the emergence of space physics and to put the events into a professional as well as personal perspective." (Gombosi et al.,1994). The authors of this special collection of recollections were selected following the same guidelines as the previous efforts. We started from a long list of senior colleagues and narrowed the list to roughly two dozen distinguished scientists based on discipline and geographic balance. Some of our colleagues, when asked, felt they would be unable to devote the time or energy to such a recollection and declined. Sadly,in the intervening 25 years since the original effort, some of our colleagues who were most active during the early years of the space age have passed. Therefore, this new special collection, 25 years after the first one, is timely with the AGU centennial celebrations, but late in fully capturing the stories of the pioneers of space physics. This is unfortunate and we encourage future editors of this journal to commission specialsections of legacy perspectives with a faster cadence than a quarter of a century.

Kepko, Emil L.↗

MIND-MAC: Multi-Level In-memory Quasi Non-Destructive MAC Operation in Compact 2T-nC FeRAM for Efficient DNN Accelerator

We present MIND-MAC, a compact 2T-nC FeRAM architecture that performs multi-level, quasi-non-destructive in-memory multiply–accumulate (MAC) for deep neural networks. By exploiting voltage-controlled partial domain switching in MFM capacitors and read-transistor amplification, the cell stores multi-bit weights and gates bit-serial inputs to produce an accumulated current on shared lines. We combine TCAD-extracted parasitics with experimentally calibrated ferroelectric models in SPICE to validate device-/circuit-level behavior, and validate multi-level sensing and QNRO with measurements on a fabricated 2T-3C test vehicle. An analytical system model maps MIND-MAC to a 6-GB main-memory in-memory compute (IMC) architecture and benchmarks VGG13 inference in 61.08 ms at 964.99 mJ. Results indicate high density, reduced rewrite overhead, and energy efficiency, positioning 2T-nC FeRAM as a promising IMC candidate for next-generation AI hardware.

36 MATERIALS SCIENCE↗

Open-Source Contributions to Arbiter2

Login nodes at High-Performance Computing (HPC) sites are shared resources used by a multitude of users to compile, test and submit jobs to the batch system. Because these nodes are shared by multiple users at any time, if a minority of users are using a significant proportion of the resources of the node (CPU, memory, etc.), other users' tasks may be negatively impacted. Arbiter2 is an open-source project developed by the University of Utah that aims to prevent these occurrences by dynamically limiting the resources of users depending on whether they are excessively using resources. INL has sought to adapt and develop Arbiter2 for a potential deployment at INL and plans on upstreaming the changes and improvements so that other HPC sites running Arbiter2 can benefit from their work.

97 MATHEMATICS AND COMPUTING↗

Improvements to a Batch Pentadiagonal Solver on NVIDIA GPUs

This poster presents the recent work in OVERFLOW to port the batched pentadiagonal solver to NVIDIA GPUs. There are five pentadiagonal systems for each pencil in the grid but three of these systems share the same LHS. Our first simple approach for porting the pentadiagonal solver to the GPUs was to take advantage of the shared LHS by assigning three threads to the three LHS of each pencil. We demonstrated that this custom solver was 92% faster than the NVIDIA batched pentadiagonal library implementation on a V100 GPU due to the lower memory bandwidth requirements. The second approach treated each pentadiagonal system as a 2x2 block tridiagonal system and used a variant of the parallel cyclic reduction algorithm to solve the problem. One benefit of this approach is that it does not require interleaving the data between each system. We demonstrated that this algorithm is 2.18x faster than the NVIDIA library implementation for the same amount of work. If we take advantage of our shared LHS, this approach is 2.58x faster than the library implementation on a V100 GPU.

GPU Programming↗

Virtualized Logical Qubits: A 2.5D Architecture for Error-Corrected Quantum Computing

Current, near-term quantum devices have shown great progress in the last several years culminating recently with a demonstration of quantum supremacy. In the medium-term, however, quantum machines will need to transition to greater reliability through error correction, likely through promising techniques like surface codes which are well suited for near-term devices with limited qubit connectivity. We discover quantum memory, particularly resonant cavities with transmon qubits arranged in a 2.5D architecture, can efficiently implement surface codes with substantial hardware savings and performance/fidelity gains. Specifically, we virtualize logical qubits by storing them in layers of qubit memories connected to each transmon. Surprisingly, distributing each logical qubit across many memories has a minimal impact on fault tolerance and results in substantially more efficient operations. Our design permits fast transversal application of CNOT operations between logical qubits sharing the same physical address (same set of cavities) which are 6x faster than standard lattice surgery CNOTs. We develop a novel embedding which saves approximately 10x in transmons with another 2x savings from an additional optimization for compactness. Although qubit virtualization pays a 10x penalty in serialization, advantages in the transversal CNOT and in area efficiency result in fault-tolerance and performance comparable to conventional 2D transmon-only architectures. Our simulations show our system can achieve fault tolerance comparable to conventional two-dimensional grids while saving substantial hardware. Furthermore, our architecture can produce magic states at 1.22x the baseline rate given a fixed number of transmon qubits. Here, this is a critical benchmark for future fault-tolerant quantum computers as magic states are essential and machines will spend the majority of their resources continuously producing them. This architecture substantially reduces the hardware requirements for fault-tolerant quantum computing and puts within reach a proof-of-concept experimental demonstration of around 10 logical qubits, requiring only 11 transmons and 9 attached cavities in total.

quantum computing↗

Jell-Molds and Cookie-cutters: Shrinkwrap Isn't Just for Leftovers Anymore

So what is Shrinkwrap all about? For those of you who may not know about it, Shrinkwrap is a type of data structure that can manifest itself as a feature or model. It is cleverly covered up, almost hidden, and doesn't get the press or widespread use of a solid or surface. The shrinkwrap feature is located under the data sharing submenu of the feature menu. The shrinkwrap feature, as described by PTC, is a collection of surfaces and datum features of a model that represents the exterior of the model . The advantages and applications of the shrinkwrap feature are in the creation of minimal memory guzzling representations of assemblies. These can be used to represent subassemblies in parent assemblies, and can handle control of dependency issues, geometry represented, and additional references through the use of the shrinkwrap feature options. The shrinkwrap model is an option available under the save as umbrella. Its function, as described by PTC, is to share data with internal and external design groups and improve performance in large assembly design . Some of the benefits of the shrinkwrap model include being able to represent complex assemblies with a single, lightweight part that protects design intent and parametric data, and the ability to improve performance of large assembly modeling in the area of less load time. The proper-scale models can be saved as IGES, STEP, and VRML (for fly-throughs).

Randazzo, John↗

Design and analysis of CXL performance models for tightly-coupled heterogeneous computing

Truly heterogeneous systems enable partitioned workloads to be mapped to the hardware that nets the best performance. However, current practice requires that inter-device communication between different vendors' hardware use host memory as an intermediary step. To date, there are no widely adopted solutions that allow accelerators to directly transfer data. A new cache-coherent protocol, CXL, aims to facilitate easier, fine-grained sharing between accelerators. In this work we analyze existing methods for designing heterogeneous applications that target GPUs and FPGAs working collaboratively, followed by an exploration to show the benefits of a CXL-enabled system. Specifically, we develop a test application that utilizes both an NVIDIA P100 GPU and a Xilinx U250 FPGA to show current communication limitations. From this application, we capture overall execution time and throughput measurements on the FPGA and GPU. We use these measurements as inputs to novel CXL performance models to show that using CXL caching instead of host memory results in a 1.31X speedup, while a more tightly-coupled pipelined implementation using CXL-enabled hardware would result in a speedup of 1.45X.

Cabrera, Anthony↗

The SONATA data format for efficient description of large-scale network models

Increasing availability of comprehensive experimental datasets and of high-performance computing resources are driving rapid growth in scale, complexity, and biological realism of computational models in neuroscience. To support construction and simulation, as well as sharing of such large-scale models, a broadly applicable, flexible, and high-performance data format is necessary. To address this need, we have developed the Scalable Open Network Architecture TemplAte (SONATA) data format. It is designed for memory and computational efficiency and works across multiple platforms. The format represents neuronal circuits and simulation inputs and outputs via standardized files and provides much flexibility for adding new conventions or extensions. SONATA is used in multiple modeling and visualization tools, and we also provide reference Application Programming Interfaces and model examples to catalyze further adoption. SONATA format is free and open for the community to use and build upon with the goal of enabling efficient model building, sharing, and reproducibility.

59 BASIC BIOLOGICAL SCIENCES↗

An interlaboratory comparison of mid-infrared spectra acquisition: Instruments and procedures matter

Diffuse reflectance spectroscopy has been extensively employed to deliver timely and cost-effective predictions of a number of soil properties. However, although several soil spectral laboratories have been established worldwide, the distinct characteristics of instruments and operations still hamper further integration and interoperability across mid-infrared (MIR) soil spectral libraries. In this study, we conducted a large-scale ring trial experiment to understand the lab-to-lab variability of multiple MIR instruments. By developing a systematic evaluation of different mathematical treatments with modeling algorithms, including regular preprocessing and spectral standardization, we quantified and evaluated instruments' dissimilarity and how this impacts internal and shared model performance. We found that all instruments delivered good predictions when calibrated internally using the same instruments' characteristics and standard operating procedures by solely relying on regular spectral preprocessing that accounts for light scattering and multiplicative/additive effects, e.g., using standard normal variate (SNV). When performing model transfer from a large public library (the USDA NSSCKSSL MIR library) to secondary instruments, good performance was also achieved by regular preprocessing (e. g., SNV) if both instruments shared the same manufacturer. However, significant differences between the KSSL MIR library and contrasting ring trial instruments responses were evident and confirmed by a semi-unsupervised spectral clustering. For heavily contrasting setups, spectral standardization was necessary before transferring prediction models. Non-linear model types like Cubist and memory-based learning delivered more precise estimates because they seemed to be less sensitive to spectral variations than global partial least square regression. In summary, the results from this study can assist new laboratories in building spectroscopy capacity utilizing existing MIR spectral libraries and support the recent global efforts to make soil spectroscopy universally accessible with centralized or shared operating procedures.

58 GEOSCIENCES↗

The effects of stimulus modality and task integrality: Predicting dual-task performance and workload from single-task levels

The influence of stimulus modality and task difficulty on workload and performance was investigated. The goal was to quantify the cost (in terms of response time and experienced workload) incurred when essentially serial task components shared common elements (e.g., the response to one initiated the other) which could be accomplished in parallel. The experimental tasks were based on the Fittsberg paradigm; the solution to a SternBERG-type memory task determines which of two identical FITTS targets are acquired. Previous research suggested that such functionally integrated dual tasks are performed with substantially less workload and faster response times than would be predicted by suming single-task components when both are presented in the same stimulus modality (visual). The physical integration of task elements was varied (although their functional relationship remained the same) to determine whether dual-task facilitation would persist if task components were presented in different sensory modalities. Again, it was found that the cost of performing the two-stage task was considerably less than the sum of component single-task levels when both were presented visually. Less facilitation was found when task elements were presented in different sensory modalities. These results suggest the importance of distinguishing between concurrent tasks that complete for limited resources from those that beneficially share common resources when selecting the stimulus modalities for information displays.

Hart, S. G.↗

Rapid wavefield forecasting for earthquake early warning via deep sequence to sequence learning

We propose a deep learning model, WaveCastNet, to forecast high-dimensional wavefields. WaveCastNet integrates a convolutional long expressive memory architecture into a sequence-to-sequence forecasting framework, enabling it to model long-term dependencies and multiscale patterns in both space and time. By sharing weights across spatial and temporal dimensions, WaveCastNet requires significantly fewer parameters than more resource-intensive models such as transformers, resulting in faster inference times. Crucially, WaveCastNet also generalizes better than transformers to rare and critical seismic scenarios, such as high-magnitude earthquakes. Here, we show the ability of the model to predict the intensity and timing of destructive ground motions in real time, using simulated data from the San Francisco Bay Area. Furthermore, we demonstrate its zero-shot capabilities by evaluating WaveCastNet on real earthquake data. Our approach does not require estimating earthquake magnitudes and epicenters, steps that are prone to error in conventional methods, nor does it rely on empirical ground-motion models, which often fail to capture strongly heterogeneous wave propagation effects.

Geophysics↗

The effects of syntactic complexity on the human-computer interaction

Three divided-attention experiments were performed to evaluate the effectiveness of a syntactic analysis of the primary task of editing flight route-way-point information. For all editing conditions, a formal syntactic expression was developed for the operator's interaction with the computer. In terms of the syntactic expression, four measures of syntactic were examined. Increased syntactic complexity did increase the time to train operators, but once the operators were trained, syntactic complexity did not influence the divided-attention performance. However, the number of memory retrievals required of the operator significantly accounted for the variation in the accuracy, workload, and task completion time found on the different editing tasks under attention-sharing conditions.

Chechile, R. A.↗

General-purpose interface bus for multiuser, multitasking computer system

The architecture of a multiuser, multitasking, virtual-memory computer system intended for the use by a medium-size research group is described. There are three central processing units (CPU) in the configuration, each with 16 MB memory, and two 474 MB hard disks attached. CPU 1 is designed for data analysis and contains an array processor for fast-Fourier transformations. In addition, CPU 1 shares display images viewed with the image processor. CPU 2 is designed for image analysis and display. CPU 3 is designed for data acquisition and contains 8 GPIB channels and an analog-to-digital conversion input/output interface with 16 channels. Up to 9 users can access the third CPU simultaneously for data acquisition. Focus is placed on the optimization of hardware interfaces and software, facilitating instrument control, data acquisition, and processing.

Generazio, Edward R.↗