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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Toward a Holistic Performance Evaluation of Large Language Models Across Diverse AI Accelerators

Artificial intelligence (AI) methods have become critical in scientific applications to help accelerate scientific discovery. Large language models (LLMs) are being considered a promising approach to address some challenging problems because of their superior generalization capabilities across domains. The effectiveness of the models and the accuracy of the applications are contingent upon their efficient execution on the underlying hardware infrastructure. Specialized Al accelerator hardware systems have recently become available for accelerating Al applications. However, the comparative performance of these AI accelerators on large language models has not been previously studied. In this paper, we systematically study LLMs on multiple AI accelerators and GPUs and evaluate their performance characteristics for these models. We evaluate these systems with (i) a micro-benchmark using a core transformer block, (ii) a GPT-2 model, and (iii) an 1,I,M-driven science use case, GenSLM. We present our findings and analyses of the models' performance to better understand the intrinsic capabilities of AI accelerators. Furthermore, our analysis takes into account key factors such as sequence lengths, scaling behavior, and sensitivity to gradient accumulation steps.

Emani, Murali↗
NASA NTRS1995

File-System Workload on a Scientific Multiprocessor

Many scientific applications have intense computational and I/O requirements. Although multiprocessors have permitted astounding increases in computational performance, the formidable I/O needs of these applications cannot be met by current multiprocessors a their I/O subsystems. To prevent I/O subsystems from forever bottlenecking multiprocessors and limiting the range of feasible applications, new I/O subsystems must be designed. The successful design of computer systems (both hardware and software) depends on a thorough understanding of their intended use. A system designer optimizes the policies and mechanisms for the cases expected to most common in the user's workload. In the case of multiprocessor file systems, however, designers have been forced to build file systems based only on speculation about how they would be used, extrapolating from file-system characterizations of general-purpose workloads on uniprocessor and distributed systems or scientific workloads on vector supercomputers (see sidebar on related work). To help these system designers, in June 1993 we began the Charisma Project, so named because the project sought to characterize 1/0 in scientific multiprocessor applications from a variety of production parallel computing platforms and sites. The Charisma project is unique in recording individual read and write requests-in live, multiprogramming, parallel workloads (rather than from selected or nonparallel applications). In this article, we present the first results from the project: a characterization of the file-system workload an iPSC/860 multiprocessor running production, parallel scientific applications at NASA's Ames Research Center.

Kotz, David↗
NASA NTRSDate not supplied

A Comparison of Two Non-Contact Strain Measurement Techniques with Applications to Scientific Balloons

Strain measurements of scientific balloon films are necessary for evaluating the film’s material properties, validating material models, and structural evaluations of scale model balloons. This paper presents a comparison of the strain measurement techniques used by the Balloon Program Office’s Balloon Research and Development Lab at NASA Wallops Flight Facility. Two non-contact strain measurement techniques are presented for comparison, along with an assessment of measurement accuracy for both methods. The case study of a vertically oriented cylindrical balloon is presented to illustrate both systems’ performance and draw nominal conclusions of strain as a function of pressure and axial load.

Non-Contact↗
NASA NTRS1992

Automatic data partitioning on distributed memory multicomputers

Distributed-memory parallel computers are increasingly being used to provide high levels of performance for scientific applications. Unfortunately, such machines are not very easy to program. A number of research efforts seek to alleviate this problem by developing compilers that take over the task of generating communication. The communication overheads and the extent of parallelism exploited in the resulting target program are determined largely by the manner in which data is partitioned across different processors of the machine. Most of the compilers provide no assistance to the programmer in the crucial task of determining a good data partitioning scheme. A novel approach is presented, the constraints-based approach, to the problem of automatic data partitioning for numeric programs. In this approach, the compiler identifies some desirable requirements on the distribution of various arrays being referenced in each statement, based on performance considerations. These desirable requirements are referred to as constraints. For each constraint, the compiler determines a quality measure that captures its importance with respect to the performance of the program. The quality measure is obtained through static performance estimation, without actually generating the target data-parallel program with explicit communication. Each data distribution decision is taken by combining all the relevant constraints. The compiler attempts to resolve any conflicts between constraints such that the overall execution time of the parallel program is minimized. This approach has been implemented as part of a compiler called Paradigm, that accepts Fortran 77 programs, and specifies the partitioning scheme to be used for each array in the program. We have obtained results on some programs taken from the Linpack and Eispack libraries, and the Perfect Benchmarks. These results are quite promising, and demonstrate the feasibility of automatic data partitioning for a significant class of scientific application programs with regular computations.

Gupta, Manish↗
NASA NTRS1998

On the Efficacy of Source Code Optimizations for Cache-Based Systems

Obtaining high performance without machine-specific tuning is an important goal of scientific application programmers. Since most scientific processing is done on commodity microprocessors with hierarchical memory systems, this goal of "portable performance" can be achieved if a common set of optimization principles is effective for all such systems. It is widely believed, or at least hoped, that portable performance can be realized. The rule of thumb for optimization on hierarchical memory systems is to maximize temporal and spatial locality of memory references by reusing data and minimizing memory access stride. We investigate the effects of a number of optimizations on the performance of three related kernels taken from a computational fluid dynamics application. Timing the kernels on a range of processors, we observe an inconsistent and often counterintuitive impact of the optimizations on performance. In particular, code variations that have a positive impact on one architecture can have a negative impact on another, and variations expected to be unimportant can produce large effects. Moreover, we find that cache miss rates - as reported by a cache simulation tool, and confirmed by hardware counters - only partially explain the results. By contrast, the compiler-generated assembly code provides more insight by revealing the importance of processor-specific instructions and of compiler maturity, both of which strongly, and sometimes unexpectedly, influence performance. We conclude that it is difficult to obtain performance portability on modern cache-based computers, and comment on the implications of this result.

VanderWijngaart, Rob F.↗
NASA NTRS1998

On the Efficacy of Source Code Optimizations for Cache-Based Systems

Obtaining high performance without machine-specific tuning is an important goal of scientific application programmers. Since most scientific processing is done on commodity microprocessors with hierarchical memory systems, this goal of "portable performance" can be achieved if a common set of optimization principles is effective for all such systems. It is widely believed, or at least hoped, that portable performance can be realized. The rule of thumb for optimization on hierarchical memory systems is to maximize temporal and spatial locality of memory references by reusing data and minimizing memory access stride. We investigate the effects of a number of optimizations on the performance of three related kernels taken from a computational fluid dynamics application. Timing the kernels on a range of processors, we observe an inconsistent and often counterintuitive impact of the optimizations on performance. In particular, code variations that have a positive impact on one architecture can have a negative impact on another, and variations expected to be unimportant can produce large effects. Moreover, we find that cache miss rates-as reported by a cache simulation tool, and confirmed by hardware counters-only partially explain the results. By contrast, the compiler-generated assembly code provides more insight by revealing the importance of processor-specific instructions and of compiler maturity, both of which strongly, and sometimes unexpectedly, influence performance. We conclude that it is difficult to obtain performance portability on modern cache-based computers, and comment on the implications of this result.

VanderWijngaart, Rob F.↗
DOE OSTI2024

Anderson acceleration with approximate calculations: Applications to scientific computing

Here we provide rigorous theoretical bounds for Anderson acceleration (AA) that allow for approximate calculations when applied to solve linear problems. We show that, when the approximate calculations satisfy the provided error bounds, the convergence of AA is maintained while the computational time could be reduced. We also provide computable heuristic quantities, guided by the theoretical error bounds, which can be used to automate the tuning of accuracy while performing approximate calculations. For linear problems, the use of heuristics to monitor the error introduced by approximate calculations, combined with the check on monotonicity of the residual, ensures the convergence of the numerical scheme within a prescribed residual tolerance. Motivated by the theoretical studies, we propose a reduced variant of AA, which consists in projecting the least-squares used to compute the Anderson mixing onto a subspace of reduced dimension. The dimensionality of this subspace adapts dynamically at each iteration as prescribed by the computable heuristic quantities. We numerically show and assess the performance of AA with approximate calculations on: (i) linear deterministic fixed-point iterations arising from the Richardson's scheme to solve linear systems with open-source benchmark matrices with various preconditioners and (ii) non-linear deterministic fixed-point iterations arising from non-linear time-dependent Boltzmann equations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

What do physics-informed DeepONets learn? Understanding and improving training for scientific computing applications

Physics-informed deep operator networks (DeepONets) have emerged as a promising approach toward numerically approximating the solution of partial differential equations (PDEs). In this work, we aim to develop further understanding of what is being learned by physics-informed DeepONets by assessing the universality of the extracted basis functions and demonstrating their potential toward model reduction with spectral methods. Results provide clarity about measuring the performance of a physics-informed DeepONet through the decays of singular values and expansion coefficients. In addition, we propose a transfer learning approach for improving training for physics-informed DeepONets between parameters of the same PDE as well as across different, but related, PDEs where these models struggle to train well. This approach results in significant error reduction and learned basis functions that are more effective in representing the solution of a PDE.

Deep operator networks↗
DOE OSTI2021

Forged Ingot Niobium Technology for Accelerator Applications and Scientific Frontiers

We report the rf performance of several single-cell superconducting radiofrequency cavities frequency ranging from 1.3-3.0 GHz after low temperature baking in nitrogen environment The cavities are treated at different temperature in the range of (120-160oC) for extended period of time (~24-48 hours) with nitrogen gas injection in the furnace. The improvement in Q0 with Q-rise in some case was observed when nitrogen gas was injected at elevated temperature (~250-290 oC) and held at the temperature range 120-200 oC without any degradation in accelerating gradient over the baseline performance. The temperature and time of baking play significant role in dependence of quality factor on accelerating gradient.

Khanal, B.↗
NASA NTRS1986

Tunable solid-state laser technology for applications to scientific and technological experiments from space

Current plans for the Earth Observing System (EOS) include development of a lidar facility to conduct scientific experiments from a polar orbiting platforms. A recommended set of experiments were scoped, which includes techniques of atmospheric backscatter (Lidar), Differential Absorption Lidar (DIAL), altimetry, and retroranging. Preliminary assessments of the resources (power, weight, volume) required by the Eos Lidar Facility were conducted. A research program in tunable solid state laser technology was developed, which includes laser materials development, modeling and experiments on the physics of solid state laser materials, and development of solid state laser transmitters with a strong focus on Eos scientific investigations. Some of the system studies that were conducted which highlight the payoff of solid state laser technology for the Eos scientific investigations will be discussed. Additionally, a summary of some promising research results which have recently emerged from the research program will be presented.

Allario, F.↗
NASA NTRS1988

Lessons learned in ground processing scientific and applications payloads at Kennedy Space Center

The payload ground processing of experiments which flew on the Shuttle is examined, including studies of atmosphere and earth observation, life science, advance technology, materials science, plasma physics, astrophysics and solar physics, astronomy, navigation and communication, and fluid mechanics. The process of designing and development payloads, the integration of instruments, carrier interface verification, and late servicing at the launch pad are discussed. The problems of cost, red tape, contamination, safety, and propriety protection are considered.

Elfrey, Priscilla↗
NASA NTRS1993

Lunar scout missions: Galileo encounter results and application to scientific problems and exploration requirements

The Lunar Scout Missions (payload: x-ray fluorescence spectrometer, high-resolution stereocamera, neutron spectrometer, gamma-ray spectrometer, imaging spectrometer, gravity experiment) will provide a global data set for the chemistry, mineralogy, geology, topography, and gravity of the Moon. These data will in turn provide an important baseline for the further scientific exploration of the Moon by all-purpose landers and micro-rovers, and sample return missions from sites shown to be of primary interest from the global orbital data. These data would clearly provide the basis for intelligent selection of sites for the establishment of lunar base sites for long-term scientific and resource exploration and engineering studies. The two recent Galileo encounters with the Moon (December, 1990 and December, 1992) illustrate how modern technology can be applied to significant lunar problems. We emphasize the regional results of the Galileo SSI to show the promise of geologic unit definition and characterization as an example of what can be done with the global coverage to be obtained by the Lunar Scout Missions.

Head, J. W.↗
NASA NTRS2004

Optical Strain Measurement of an Inflated Cylinder using Photogrammetry with Application to Scientific Balloons

A study is presented using photogrammetry to measure the biaxial strain in an inflated cylinder. Two cylinders constructed from polyethylene and each approximately 222 mm in diameter and 930 mm in length were studied. The first had a 0.038 mm wall thickness while the second had a 0.02 mm wall thickness. The cylinders were inflated to a maximum pressure of 1379 Pa. The strain was determined from data collected from 60 retro-reflective targets arranged in a 12 x 5 grid. The uncertainty of the measurement system was determined to be 0.08, 0.04 and 0.06 mm in the x, y, and z directions respectively. The hoop and meridional strains determined from displacement data were compared to values obtained from a finite element analysis of a related proxy problem. The predicted hoop strains showed good agreement over the entire range of pressures while the meridional strains showed good agreement at the lower pressures.

Blandino, Joseph R.↗