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Book ; Online: A Multi-Level, Multi-Scale Visual Analytics Approach to Assessment of Multifidelity HPC Systems

Shilpika / Lusch, Bethany / Emani, Murali / Simini, Filippo / Vishwanath, Venkatram / Papka, Michael E. / Ma, Kwan-Liu

2023

Abstract: The ability to monitor and interpret of hardware system events and behaviors are crucial to improving the robustness and reliability of these systems, especially in a supercomputing facility. The growing complexity and scale of these systems demand an ... ...

Abstract	The ability to monitor and interpret of hardware system events and behaviors are crucial to improving the robustness and reliability of these systems, especially in a supercomputing facility. The growing complexity and scale of these systems demand an increase in monitoring data collected at multiple fidelity levels and varying temporal resolutions. In this work, we aim to build a holistic analytical system that helps make sense of such massive data, mainly the hardware logs, job logs, and environment logs collected from disparate subsystems and components of a supercomputer system. This end-to-end log analysis system, coupled with visual analytics support, allows users to glean and promptly extract supercomputer usage and error patterns at varying temporal and spatial resolutions. We use multiresolution dynamic mode decomposition (mrDMD), a technique that depicts high-dimensional data as correlated spatial-temporal variations patterns or modes, to extract variation patterns isolated at specified frequencies. Our improvements to the mrDMD algorithm help promptly reveal useful information in the massive environment log dataset, which is then associated with the processed hardware and job log datasets using our visual analytics system. Furthermore, our system can identify the usage and error patterns filtered at user, project, and subcomponent levels. We exemplify the effectiveness of our approach with two use scenarios with the Cray XC40 supercomputer.
Keywords	Computer Science - Human-Computer Interaction ; Computer Science - Computer Vision and Pattern Recognition
Subject code	006
Publishing date	2023-06-15
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: Hybrid Workload Scheduling on HPC Systems

Fan, Yuping / Rich, Paul / Allcock, William / Papka, Michael / Lan, Zhiling

2021

Abstract: Traditionally, on-demand, rigid, and malleable applications have been scheduled and executed on separate systems. The ever-growing workload demands and rapidly developing HPC infrastructure trigger the interest of converging these applications on a ... ...

Abstract	Traditionally, on-demand, rigid, and malleable applications have been scheduled and executed on separate systems. The ever-growing workload demands and rapidly developing HPC infrastructure trigger the interest of converging these applications on a single HPC system. Although allocating the hybrid workloads within one system could potentially improve system efficiency, it is difficult to balance the tradeoff between the responsiveness of on-demand requests, the incentive for malleable jobs, and the performance of rigid applications. In this study, we present several scheduling mechanisms to address the issues involved in co-scheduling on-demand, rigid, and malleable jobs on a single HPC system. We extensively evaluate and compare their performance under various configurations and workloads. Our experimental results show that our proposed mechanisms are capable of serving on-demand workloads with minimal delay, offering incentives for declaring malleability, and improving system performance.
Keywords	Computer Science - Distributed ; Parallel ; and Cluster Computing
Subject code	000
Publishing date	2021-09-11
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: A Comprehensive Performance Study of Large Language Models on Novel AI Accelerators

Emani, Murali / Foreman, Sam / Sastry, Varuni / Xie, Zhen / Raskar, Siddhisanket / Arnold, William / Thakur, Rajeev / Vishwanath, Venkatram / Papka, Michael E.

2023

Abstract: Artificial intelligence (AI) methods have become critical in scientific applications to help accelerate scientific discovery. Large language models (LLMs) are being considered as a promising approach to address some of the challenging problems because of ...

Abstract	Artificial intelligence (AI) methods have become critical in scientific applications to help accelerate scientific discovery. Large language models (LLMs) are being considered as a promising approach to address some of the challenging problems because of their superior generalization capabilities across domains. The effectiveness of the models and the accuracy of the applications is contingent upon their efficient execution on the underlying hardware infrastructure. Specialized AI accelerator hardware systems have recently become available for accelerating AI 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 LLM-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, sparsity, and sensitivity to gradient accumulation steps.
Keywords	Computer Science - Performance ; Computer Science - Artificial Intelligence ; Computer Science - Hardware Architecture ; Computer Science - Machine Learning
Subject code	006
Publishing date	2023-10-06
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Extending the Hoyle-State Paradigm to ^{12}C+^{12}C Fusion.

Adsley, P / Heine, M / Jenkins, D G / Courtin, S / Neveling, R / Brümmer, J W / Donaldson, L M / Kheswa, N Y / Li, K C W / Marín-Lámbarri, D J / Mabika, P Z / Papka, P / Pellegri, L / Pesudo, V / Rebeiro, B / Smit, F D / Yahia-Cherif, W

Physical review letters

2022 Volume 129, Issue 10, Page(s) 102701

Abstract: Carbon burning is a key step in the evolution of massive stars, Type 1a supernovae and superbursts in x-ray binary systems. Determining the ^{12}C+^{12}C fusion cross section at relevant energies by extrapolation of direct measurements is challenging due ...

Abstract	Carbon burning is a key step in the evolution of massive stars, Type 1a supernovae and superbursts in x-ray binary systems. Determining the ^{12}C+^{12}C fusion cross section at relevant energies by extrapolation of direct measurements is challenging due to resonances at and below the Coulomb barrier. A study of the ^{24}Mg(α,α^{'})^{24}Mg reaction has identified several 0^{+} states in ^{24}Mg, close to the ^{12}C+^{12}C threshold, which predominantly decay to ^{20}Ne(ground state)+α. These states were not observed in ^{20}Ne(α,α_{0})^{20}Ne resonance scattering suggesting that they may have a dominant ^{12}C+^{12}C cluster structure. Given the very low angular momentum associated with sub-barrier fusion, these states may play a decisive role in ^{12}C+^{12}C fusion in analogy to the Hoyle state in helium burning. We present estimates of updated ^{12}C+^{12}C fusion reaction rates.
Language	English
Publishing date	2022-09-16
Publishing country	United States
Document type	Journal Article
ZDB-ID	208853-8
ISSN	1079-7114 ; 0031-9007
ISSN (online)	1079-7114
ISSN	0031-9007
DOI	10.1103/PhysRevLett.129.102701
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Book ; Online: Scaling Computational Fluid Dynamics

Mateevitsi, Victor A. / Bode, Mathis / Ferrier, Nicola / Fischer, Paul / Göbbert, Jens Henrik / Insley, Joseph A. / Lan, Yu-Hsiang / Min, Misun / Papka, Michael E. / Patel, Saumil / Rizzi, Silvio / Windgassen, Jonathan

In Situ Visualization of NekRS using SENSEI

2023

Abstract: In the realm of Computational Fluid Dynamics (CFD), the demand for memory and computation resources is extreme, necessitating the use of leadership-scale computing platforms for practical domain sizes. This intensive requirement renders traditional ... ...

Abstract	In the realm of Computational Fluid Dynamics (CFD), the demand for memory and computation resources is extreme, necessitating the use of leadership-scale computing platforms for practical domain sizes. This intensive requirement renders traditional checkpointing methods ineffective due to the significant slowdown in simulations while saving state data to disk. As we progress towards exascale and GPU-driven High-Performance Computing (HPC) and confront larger problem sizes, the choice becomes increasingly stark: to compromise data fidelity or to reduce resolution. To navigate this challenge, this study advocates for the use of in situ analysis and visualization techniques. These allow more frequent data "snapshots" to be taken directly from memory, thus avoiding the need for disruptive checkpointing. We detail our approach of instrumenting NekRS, a GPU-focused thermal-fluid simulation code employing the spectral element method (SEM), and describe varied in situ and in transit strategies for data rendering. Additionally, we provide concrete scientific use-cases and report on runs performed on Polaris, Argonne Leadership Computing Facility's (ALCF) 44 Petaflop supercomputer and J\"ulich Wizard for European Leadership Science (JUWELS) Booster, J\"ulich Supercomputing Centre's (JSC) 71 Petaflop High Performance Computing (HPC) system, offering practical insight into the implications of our methodology.
Keywords	Computer Science - Distributed ; Parallel ; and Cluster Computing ; Computer Science - Performance
Subject code	000
Publishing date	2023-12-15
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: GEOMORPHOLOGICAL ECOGEOGRAPHICAL VARIABLES DEFINIG FEATURES OF ECOLOGICAL NICHE OF COMMON MILKWEED (ASCLEPIAS SYRIACA L.)

O. M. Kunah / O. S. Papka

Bìologìčnij Vìsnik Melìtopolʹsʹkogo Deržavnogo Pedagogìčnogo Universitetu Imenì Bogdana Hmelʹnicʹkogo, Vol 6, Iss 01, Pp 243-

2016 Volume 275

Abstract: The role of geomorphological ecogeographical variables have been shown, which are received by means of the digital elevation model created on the basis of remote sensing data as markers of an ecological niche of weeds on an example common milkweed ( ... ...

Abstract	The role of geomorphological ecogeographical variables have been shown, which are received by means of the digital elevation model created on the basis of remote sensing data as markers of an ecological niche of weeds on an example common milkweed (Asclepias syriaca L.). The research range chooses territory which is in settlement Vovnjanka district (the Poltava region). The range has the linear sizes of 26 kilometres in a direction from the east on the west and 15 kilometres in a direction from the north on the south, the range total area makes 390 км2. As geomorphological variables the topographical wetness index, topographic position index, mass balance index, erosion LS-factor, direct and disseminated insolation, altitude above channel network, multiresolution valley bottom flatness, multiresolution ridge top flatness index, vector ruggedness measure have been considered. It is established, that on set of the geomorphological indicators received by means of digital model of a relief, it is possible to assert, that within a separate agricultural field a wide variety of microconditions which is caused by relief features is formed. Possibly, the variation of thermal and water modes, moisture redistribution, and also productivity mechanical processings of soil and efforts under the control of number of weeds make a background in which limits there is possible a moving of weed plants, including common milkweed.
Keywords	ваточник сирийский ; цифровая модель рельефа ; экологическая ниша ; дистанционное зондирование Земли ; Biology (General) ; QH301-705.5
Language	English
Publishing date	2016-04-01T00:00:00Z
Publisher	Bogdan Chmelnitskiy Melitopol State Pedagogical University
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Ecogeographical determinants of the ecological niche of the common milkweed (Asclepias syriaca) on the basis of indices of remote sensing of land images

O. M. Kunah / O. S. Papka

Vìsnik Dnìpropetrovsʹkogo Unìversitetu: Serìâ Bìologìâ, Ekologìâ, Vol 24, Iss 1, Pp 78-

2016 Volume 86

Abstract: The patterns of variation in vegetative indices received by means of data of remote land sensing are described as being dependant on geomorphological predictors and the sizes of agricultural fields in an experimental polygon within Poltava region. The ... ...

Abstract	The patterns of variation in vegetative indices received by means of data of remote land sensing are described as being dependant on geomorphological predictors and the sizes of agricultural fields in an experimental polygon within Poltava region. The possibilities of application of vegetative indices have been explored through ecogeographical determinants of the ecological niche of the common milkweed (Asclepias syriaca L.) and other weeds. On the basis of images of the land surface taken on 23 March and 27 August 2015 by the sensor control Operational Land Imager (OLI), installed on the satellite Landsat 8, vegetative indices have been calculated (AC-Index – aerosol/coastal index, Hydrothermal Composite, NDTI – Normalized Difference Tillage Index, NDVI – Normalized Difference Vegetation Index, VI – Vegetation Index, MNDW – Modified Normalized Difference Water Index, LSWI – Land Surface Water Index, NBR – Normalized Burn Ratio, M15). The data obtained have been subjected to principal component analysis and the revealed principal components have been interpreted with the help of regression analysis, in which geomorphological variables have been applied as predictors. It was possible to explain the trends of variability of the vegetative cover, formalized in the form of the principal component, by means of indices which quantitatively characterise features of relief. The various aspects of variation of vegetative cover have been shown to be characterised by the specificity of the influence of relief factors. A prominent aspect of the variation of the vegetative cover of agroecosystems is variability within a field. The degree of a variation of conditions is proportional to the size of a field. Large fields occupy level plain positions. In turn, within small fields sources of variation are changes in ecological conditions which arise owing to unevenness of relief, which increases in proximity to gullies and ravines. We have identified the aspects of the variation of vegetative cover which by their nature can be ...
Keywords	vegetative indices ; NDVI ; principal component analysis ; digital model of relief ; Biology (General) ; QH301-705.5
Subject code	910
Language	English
Publishing date	2016-03-01T00:00:00Z
Publisher	Oles Honchar Dnipropetrovsk National University
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: GenSLMs: Genome-scale language models reveal SARS-CoV-2 evolutionary dynamics.

Zvyagin, Maxim / Brace, Alexander / Hippe, Kyle / Deng, Yuntian / Zhang, Bin / Bohorquez, Cindy Orozco / Clyde, Austin / Kale, Bharat / Perez-Rivera, Danilo / Ma, Heng / Mann, Carla M / Irvin, Michael / Pauloski, J Gregory / Ward, Logan / Hayot-Sasson, Valerie / Emani, Murali / Foreman, Sam / Xie, Zhen / Lin, Diangen /

Shukla, Maulik / Nie, Weili / Romero, Josh / Dallago, Christian / Vahdat, Arash / Xiao, Chaowei / Gibbs, Thomas / Foster, Ian / Davis, James J / Papka, Michael E / Brettin, Thomas / Stevens, Rick / Anandkumar, Anima / Vishwanath, Venkatram / Ramanathan, Arvind

bioRxiv : the preprint server for biology

2022

Abstract: We seek to transform how new and emergent variants of pandemic-causing viruses, specifically SARS-CoV-2, are identified and classified. By adapting large language models (LLMs) for genomic data, we build genome-scale language models (GenSLMs) which can ... ...

Abstract	We seek to transform how new and emergent variants of pandemic-causing viruses, specifically SARS-CoV-2, are identified and classified. By adapting large language models (LLMs) for genomic data, we build genome-scale language models (GenSLMs) which can learn the evolutionary landscape of SARS-CoV-2 genomes. By pre-training on over 110 million prokaryotic gene sequences and fine-tuning a SARS-CoV-2-specific model on 1.5 million genomes, we show that GenSLMs can accurately and rapidly identify variants of concern. Thus, to our knowledge, GenSLMs represents one of the first whole genome scale foundation models which can generalize to other prediction tasks. We demonstrate scaling of GenSLMs on GPU-based supercomputers and AI-hardware accelerators utilizing 1.63 Zettaflops in training runs with a sustained performance of 121 PFLOPS in mixed precision and peak of 850 PFLOPS. We present initial scientific insights from examining GenSLMs in tracking evolutionary dynamics of SARS-CoV-2, paving the path to realizing this on large biological data.
Language	English
Publishing date	2022-11-23
Publishing country	United States
Document type	Preprint
DOI	10.1101/2022.10.10.511571
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Article: P2X receptors in the rat uterine cervix, lumbosacral dorsal root ganglia, and spinal cord during pregnancy.

Papka, Raymond E / Hafemeister, Jen / Storey-Workley, Megan

Cell and tissue research

2005 Volume 321, Issue 1, Page(s) 35–44

Abstract: ATP, an intracellular energy source, is released from cells during tissue stress, damage, or inflammation. The P2X subtype of the ATP receptor is expressed in rat dorsal root ganglion (DRG) cells, spinal cord dorsal horn, and axons in peripheral tissues. ...

Abstract	ATP, an intracellular energy source, is released from cells during tissue stress, damage, or inflammation. The P2X subtype of the ATP receptor is expressed in rat dorsal root ganglion (DRG) cells, spinal cord dorsal horn, and axons in peripheral tissues. ATP binding to P2X receptors on nociceptors generates signals that can be interpreted as pain from damaged tissue. We have hypothesized that tissue stress or damage in the uterine cervix during late pregnancy and parturition can lead to ATP release and sensory signaling via P2X receptors. Consequently, we have examined sensory pathways from the cervix in nonpregnant and pregnant rats for the presence of purinoceptors. Antiserum against the P2X3-receptor subtype showed P2X3- receptor immunoreactivity in axon-like structures of the cervix, in small and medium-sized neurons in the L6/S1 DRG, and in lamina II of the L6/S1 spinal cord segments. Retrograde tracing confirmed the projections of axons of P2X3-receptor-immunoreactive DRG neurons to the cervix. Some P2X3-receptor-positive DRG neurons also expressed estrogen receptor-alpha immunoreactivity and expressed the phosphorylated form of cyclic AMP response-element-binding protein at parturition. Western blots showed a trend toward increases of P2X3-receptor protein between pregnancy (day 10) and parturition (day 22-23) in the cervix, but no significant changes in the DRG or spinal cord. Since serum estrogen rises over pregnancy, estrogen may influence purinoceptors in these DRG neurons. We suggest that receptors responsive to ATP are expressed in uterine cervical afferent nerves that transmit sensory information to the spinal cord at parturition.
MeSH term(s)	Animals ; Blotting, Western ; Cervix Uteri/metabolism ; Estrogen Receptor alpha/metabolism ; Female ; Frozen Sections ; Ganglia, Spinal/cytology ; Ganglia, Spinal/metabolism ; Immunohistochemistry ; Lumbosacral Region ; Pregnancy ; Rats ; Rats, Sprague-Dawley ; Receptors, Purinergic P2/metabolism ; Receptors, Purinergic P2X ; Spinal Cord/cytology ; Spinal Cord/metabolism
Chemical Substances	Estrogen Receptor alpha ; Receptors, Purinergic P2 ; Receptors, Purinergic P2X
Language	English
Publishing date	2005-07
Publishing country	Germany
Document type	Comparative Study ; Journal Article
ZDB-ID	125067-x
ISSN	1432-0878 ; 0302-766X
ISSN (online)	1432-0878
ISSN	0302-766X
DOI	10.1007/s00441-005-1114-8
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Article ; Online: Visualizing large, heterogeneous data in hybrid-reality environments.

Reda, Khairi / Febretti, Alessandro / Knoll, Aaron / Aurisano, Jillian / Leigh, Jason / Johnson, Andrew / Papka, Michael E / Hereld, Mark

IEEE computer graphics and applications

2013 Volume 33, Issue 4, Page(s) 38–48

Abstract: Constructing integrative visualizations that simultaneously cater to a variety of data types is challenging. Hybrid-reality environments blur the line between virtual environments and tiled display walls. They incorporate high-resolution, stereoscopic ... ...

Abstract	Constructing integrative visualizations that simultaneously cater to a variety of data types is challenging. Hybrid-reality environments blur the line between virtual environments and tiled display walls. They incorporate high-resolution, stereoscopic displays, which can be used to juxtapose large, heterogeneous datasets while providing a range of naturalistic interaction schemes. They thus empower designers to construct integrative visualizations that more effectively mash up 2D, 3D, temporal, and multivariate datasets.
Language	English
Publishing date	2013-07
Publishing country	United States
Document type	Journal Article ; Research Support, U.S. Gov't, Non-P.H.S.
ISSN	1558-1756
ISSN (online)	1558-1756
DOI	10.1109/MCG.2013.37
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