HPC | Kalyan Perumalla

Exascale Computing for the National Energy Grid

Sat, 01 Jan 2022 00:00:00 +0000

Exascale Computing for the Stochastic Grid Dynamics of the US national energy transmission network is a part of the Exascale Computing Project to tap the world’s largest supercomputer to solve the nation’s energy grid problems.

Exascale Computing Project

Overview

The Exascale Computing Project that enables US revolutions in technology development: scientific Discovery; health care; and energy, economic, and national security. Exascale computing will provide the capability to tackle challenges at levels of complexity and performance that previously were out of reach.

The Problem

How can we secure the national energy transmission network despite unexpected cyber attacks, natural disasters, and unpredictable load fluctuations?
How fast and far into the future can we make it resilient?
How can we ultimately achieve this at the least cost to everyone?

The Solution

Enter Exascale computing and Global Optimization.

This project attacks this nationally important problem with an unprecedented high-technology approach that relies on supercomputing to work out the very best global solutions on-the-fly, rapidly examining millions of configurations involving all the energy generators, transmission lines, event contingencies, and complex physical constraints. Very high-end algorithms implemented with sophisticated parallel processing software is designed for the state-of-the-art supercomputing hardware, combining the know-how of some of the very best minds across the US national laboratory systems, tapping a range of experts in energy domain sciences, computational optimization, numerical algorithms, high-end computing hardware, and advanced software stack organization techniques.

Organization

Sponsor: US Department of Energy (DOE)
- Office: Advanced Scientific Computing Research (ASCR)
- Program: Exascale Computing Project (ECP)
Institutions: PNNL, ORNL, ANL, LLNL, NREL
Period: 2019-2023/24

Abbreviations

PNNL = Pacific Northwest National Laboratory
ORNL = Oak Ridge National Laboratory
ANL = Argonne National Laboratory
LLNL = Lawrence Livermore National Laboratory
NREL = National Renewable Energy Laboratory
PI = Principal Investigator

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ReveR-SES: Reversible Software Execution Systems

Sat, 01 Jan 2022 00:00:00 +0000

Reversible Software Execution Systems ReveR-SES is a paradigm shift in ultra-scale computing to address the outstanding scaling challenges by enabling an entirely new, orthogonal dimension to all aspects of traditional, forward-only computing.

ReveR-SES

Overview

ReveR-SES not only provides expeditious, novel solutions to scaling problems, but also opens new, longer-term research and development directions in high performance computing.

All traditional computing is done forward-only, but never in reverse order. Only recently it has been discovered that executing codes backwards can be used to greatly increasing the efficiency and usability of high performance computing. However, rendering a program reversible is an extremely challenging endeavor. This project is focused on developing the methodologies to exploit reversibility to enable scaling applications to ultra-scale platforms with 1,000,000 processor cores.

ReveR-SES contains several novel ideas, including reversible compilers, reversible libraries, reversibility extensions to standard interfaces, as well as relation to thermodynamics, information and entropy.

Quad chart

ReveR-SES Confluence

The reversible execution paradigm represents an entirely new research direction, yet, has immediate relevance to existing DOE applications and also the potential for creation of entirely new technologies and the creation of new high-technology jobs in computing. This is due to the orthogonality of reversibility to many existing HPC dimensions.

ReveR-SES Components

Overall, the new execution paradigm provides energy savings in the short-term and better energy-efficient designs in the longer term. The reversible execution systems are directly relevant to important applications such as climate, plasma physics, and materials science simulations.

ReveR-SES was Dr. Kalyan Perumalla’s Early Career Research project 2010-2015, awarded as a single-principal investigator, $2.5 million project.

https://science.osti.gov/ascr/Community-Resources/ECRP-Awardees

Scope

To define, develop, test, and implement the paradigm of reversible software execution for exascale computing.

Primary Scientific Thrusts

Developing fundamentally new reversible computer arithmetic and logic
Designing efficient asynchronous rollback-based recovery via reversible execution
Redesigning traditional physical system models to enable reversible simulation
Reevaluating theoretical computational and energy consumption interplay.

Science Impacts

Enables new capabilities for computational science common to many areas

Extremely efficient method for fault tolerant simulations on next generation heterogeneous (CPU+GPU) systems
Solves the synchronization problem at very large scales of concurrency
Overcomes undesirable reliance on memory
- Addresses the exascale hardware problem of high ratio of computational speed to memory speed
- Computational energy reduced via reduced memory footprint
Provides the most promising approach to debugging at exascale.

Enables Theoretical Advancements

Directly relates energy of computation to computational model characteristics
Positions scientific simulations for future reversible computing hardware (adiabatic circuits, Quantum Computing).

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Organization

Sponsor: US Department of Energy (DOE)
- Office: Advanced Scientific Computing Research (ASCR)
- Program: Early Career Research Program (ECRP)
Prime: Oak Ridge National Laboratory (ORNL)

Selected Publications

Normalcy, Magic, Miracle and Error: Emergence along a Reversibility Spectrum

Formation of a butterfly from a pupa, extraction of a live dove from a magician’s empty hat, generation of new particles from high-energy particle collisions and spawning a new dream world from mind in sleep are all examples of a common, fuzzy notion called ‘emergence’. In this paper, I pin the concept of emergence to the element of surprise in a phenomenon. I categorise the various notions of emergence into three main classes. These definitions are used to explain instances of emergence, organised along a continuous spectrum as normality, magic, miracle and error.

Kalyan Perumalla

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Efficient reversible uniform and non-uniform random number generation in UNU.RAN

Reversible random number generations are useful in large-scale fault-tolerant parallel computations and parallel discrete event …

Srikanth Yoginath, Kalyan Perumalla

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Towards Reversible Basic Linear Algebra Subprograms: A Performance Study

Problems such as fault tolerance and scalable synchronization can be efficiently solved using reversibility of applications…

Kalyan Perumalla, Srikanth Yoginath

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Reverse Computation for Rollback-based Fault Tolerance in Large Parallel Systems

Reverse computation is presented here as an important future direction in addressing the challenge o…

Kalyan Perumalla, Alfred Park

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Tutorial: Introduction to Reversible Computing

This tutorial provides an introduction to the concept of reversible computing, adopting an expanded view…

Kalyan Perumalla

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Reversibly Finding the Square Root of an Integer

Here we consider a case study in reversible computing, namely, how to reversibly compute the integer square root …

Melissa Yu, Kalyan Perumalla

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Reversible Simulations of Elastic Collisions (Extended arXiv version)

Consider a system of N identical hard spherical particles moving in a d-dimensional box and undergoing elastic, possibly multi-particle, collisions…

Kalyan Perumalla, Vladimir A. Protopopescu

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Reversible Simulations of Elastic Collisions

Consider a system of N identical hard spherical particles moving in a d-dimensional box and undergoi…

Kalyan Perumalla, Vladimir A. Protopopescu

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Introduction to Reversible Computing

Few books comprehensively cover the software and programming aspects of reversible computing. Fillin…

Kalyan Perumalla

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ReveR-SES: Reversible Software Execution Systems

[Pub 137]

Kalyan Perumalla

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Discrete Event Execution and Reversibility: Challenges in the Path to Asynchrony for Massively Parallel Computing

To keep up with the increasing number of processing elements in parallel/distributed computing, traditional tightly-coupled time-stepped models…

Kalyan Perumalla

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Reversible Parallel Discrete Event Formulation of a TLM-based Radio Signal Propagation Model

Radio signal strength estimation is essential in many applications, including the design of military…

Sudip Seal, Kalyan Perumalla

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ReveR-SES: Reversible Software Execution Systems

[Pub 136] http://science.energy.gov/ascr/ascac/meetings/nov-2011/

Kalyan Perumalla

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Reversible Parallel Discrete-Event Execution of Large-scale Epidemic Outbreak Models

The spatial scale, runtime speed, and behavioral detail of epidemic outbreak simulations altogether …

Kalyan Perumalla, Sudip Seal

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Compiler-based Automation Approaches to Reverse Computation

Automation is useful to facilitate reverse code generation from normal code. Here, we describe our …

Kalyan Perumalla, Christopher Carothers

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Reversible Discrete Event Formulation and Optimistic Parallel Execution of Vehicular Traffic Models

Vehicular traffic simulations are useful in applications such as emergency planning and traffic mana…

Kalyan Perumalla, Srikanth Yoginath

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Perfect Reversal of Rejection Sampling Methods for First-Passage-Time and Similar Probability Distributions

We present a perfectly reversible method for bi-directional generation of samples from computational…

Kalyan Perumalla, Aleksandar Donev

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Network Simulation

Sat, 01 Jan 2022 00:00:00 +0000

ISBN 978-1439873403 | Morgan & Claypool | Amazon
This book covers all concepts in modeling and simulating wired and wireless computer networks using parallel computing to reach Internet-scale simulations.

Overview

Network Simulation

A detailed introduction to the design, implementation, and use of network simulation tools is presented. The requirements and issues faced in the design of simulators for wired and wireless networks are discussed. Abstractions such as packet- and fluid-level network models are covered. Several existing simulations are given as examples, with details and rationales regarding design decisions presented. Issues regarding performance and scalability are discussed in detail, describing how one can utilize distributed simulation methods to increase the scale and performance of a simulation environment. Finally, a case study of two simulation tools is presented that have been developed using distributed simulation techniques. This text is essential to any student, researcher, or network architect desiring a detailed understanding of how network simulation tools are designed, implemented, and used.

Reference

Network Simulation

A detailed introduction to the design, implementation, and use of network simulation tools is presen…

Richard Fujimoto, Kalyan Perumalla, George Riley

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Intelligent Design of Structure for Function

Sat, 01 Jan 2022 00:00:00 +0000

Intelligent Design is a novel paradigm for automated, generalized, and optimized physical structural design of 3D geometry meeting a desired function.

Intelligent Design

Overview

In engineering design, an engineer starts with an initial heuristic structure and then iteratively modifies it until it satisfies all the design requirements. This lacks a thorough theoretical basis to account for the vast design space for a given problem. All current design methods are limited or biased by historical knowledge. What if this traditional design paradigm were dropped and an entirely new, unbiased, thorough framework were adopted?

Our novel Intelligent Design is the first approach to mix additive as well as subtractive steps in intelligently exploring the design space. Furthermore, it is fundamentally delinked from the traditional necessity to start with a closely related design that has been previously proven to be suitable.

(a) Traditional approach with structural determination methods that start with (b) Solid block, and (c) Minimal connection designs

Organization

Sponsor: Laboratory-Directed Research and Development, Oak Ridge National Laboratory

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BLOCKTRI: Parallel Block Tridiagonal Solver

Sat, 01 Jan 2022 00:00:00 +0000

Our Block Tridiagonal Solver is one of the fastest parallel solvers for scientific codes, written in FORTRAN and MPI using the block cyclic algorithm, and tested with plasma equilibrium simulations for fusion energy tokamaks and astrophysics applications.

BLOCKTRI

Organization

Sponsor: US Department of Energy (DOE)
- Office: Office of Science (SC)
- Program: Fusion Energy and International Thermonuclear Experimental Reactor (ITER)
Prime: Oak Ridge National Laboratory (ORNL)

Selected Publications

Bcyclic: A Parallel Block Tri-diagonal Matrix Cyclic Solver

A block tri-diagonal matrix is factored with minimal fill-in using a cyclic reduction algorithm that…

Steven Hirshman, Kalyan Perumalla, Vickie Lynch, Raul Sanchez

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Revisiting Cyclic Reduction and Parallel Prefix-Based Algorithms for Tri-diagonal Systems of Equations

Direct solvers based on prefix computation and cyclic reduction algorithms exploit the special struc…

Sudip Seal, Kalyan Perumalla, Steven Hirshman

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Scaling the SIESTA Magnetohydrodynamics Equilibrium Code

We report the results of a scaling effort that increases both the speed and resolution of the SIESTA…

Sudip Seal, Kalyan Perumalla, Steven Hirshman

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Improved Parallelization of the SIESTA Magneto-hydrodynamic Equilibrium Code Using Cyclic Reduction

SIESTA is a parallel three-dimensional plasma equilibrium code capable of resolving magnetic islands…

Sudip Seal, Steven Hirshman, Kalyan Perumalla

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Efficient Heterogeneous Execution on Large Multicore and Accelerator Platforms: Case Study Using a Block Tridiagonal Solver

The algorithmic and implementation principles are explored in gainfully exploiting GPU accelerators in conjunction with multicore processors on high-end systems…

Alfred Park, Kalyan Perumalla

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NetWarp

Sat, 01 Jan 2022 00:00:00 +0000

NetWarp is a novel time-synchronized virtual machine(VM)-based parallel simulation framework that accurately lifts the devices and the network communications to a virtual time plane while retaining full fidelity.

NetWarp

Organization

Sponsors: US Department of Defense
- Office: Army Research Laboratory (ARL)
- Office: Missile Defense Agency (MDA)
- Programs: Computational Sciences, STTR
Prime: Oak Ridge National Laboratory (ORNL)

Gallery

summary: Secure Virtual Environment for Cyber Resiliency Validation building on NetWarp technology for cybersecurity in hardware and software of missile defense systems

Virtual Machine-Based Simulation Platform For MANET-Based Cyber Infrastructure

In modeling and simulating complex systems such as mobile ad-hoc networks (MANETs) in defense communications, …

Srikanth Yoginath, Kalyan Perumalla, Brian Henz

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Taming Wild Horses: The Need for Virtual Time-based Scheduling of VMs in Network Simulations

The next generation of scalable network simulators employ virtual machines (VMs) to act as high-fidelity models of traffic producer/consumer nodes…

Srikanth Yoginath, Kalyan Perumalla, Brian Henz

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Optimized Hypervisor Scheduler for Parallel Discrete Event Simulations on Virtual Machine Platforms

With the advent of virtual machine (VM)-based platforms for parallel computing, it is now possible to execute parallel discrete event simulations (PDES)…

Srikanth Yoginath, Kalyan Perumalla

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Rocks3D-HPC

Sat, 01 Jan 2022 00:00:00 +0000

Rocks3D-HPC is an efficient parallelization of the Rocks3D high-fidelity earth moving equipment simulation based on the Discrete Element Method implemented using FORTRAN, OpenMP multi-threading, and message passing interface (MPI) for high performance computing.

Organization

Sponsor: Caterpillar, Inc.
Institutions: ORNL

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MutEnt

Fri, 15 Apr 2022 00:00:00 +0000

Mutual Entropy-based Image Registration

Overview

MutEnt

Organization

Sponsor: Department of Defense

Computing a Non-trivial Lower Bound on the Joint Entropy between Two Images

In this report, a non-trivial lower bound on the joint entropy of two non-identical images is developed, which is greater than the …

Kalyan Perumalla

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Computational Speed and Matching Quality using an Upper Bound on the Normalized Mutual Information

URL

Kalyan Perumalla, Maksudul Alam, Devin A White

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RealSim: Real-Time Simulations

Sat, 01 Jan 2022 00:00:00 +0000

Real-time Simulations is a simulation framework for fast evaluation of national emergency scenarios such as hurricanes, evaluated with large data streams and real-time computation on the latest hardware platforms on the edge.

RealSim

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Organization

Sponsor: Department of Homeland Security (DHS)
Period: 2006-2009

Towards Highly Interactive, GPU-based Evaluation of Evacuation Transport Scenarios at State-Scale

In large-scale scenarios, transportation modeling and simulation is severely constrained by simulati…

Kalyan Perumalla, Brandon Aaby, Srikanth Yoginath, Sudip Seal

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Towards Highly Interactive, GPU-based Evaluation of Evacuation Transport Scenarios at State-Scale

In large-scale scenarios, transportation modeling and simulation is severely constrained by simulati…

Kalyan Perumalla, Brandon Aaby, Srikanth Yoginath, Sudip Seal

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An Analysis Approach to Large-Scale Vehicular Network Simulations

[Pub 28]

Kalyan Perumalla, Martin Beckerman

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On Accounting for the Interplay of Kinetic and Non-Kinetic Aspects of Population Mobility Models

[Pub 31]

Kalyan Perumalla

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Efficient Simulation of Agent-Based Models on Multi-GPU and Multi-Core Clusters

An effective latency-hiding mechanism is presented in the parallelization of agent-based model simul…

Brandon Aaby, Kalyan Perumalla, Sudip Seal

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Computational Spectrum of Agent Model Simulation

The study of human social behavioral systems is finding renewed interest in military, homeland secur…

Kalyan Perumalla

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A Connectionist Modeling Approach to Rapid Analysis of Emergent Social Cognition Properties in Large-Populations

Traditional modeling methodologies, such as those based on rule-based agent modeling, are exhibiting…

Kalyan Perumalla, Jack C. Schryver

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Data Parallel Execution Challenges and Runtime Performance of Agent Simulations on GPUs

[Pub 27]

Kalyan Perumalla, Brandon Aaby

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A Case Study of Efficient Social Network Simulation through General Processing on Graphics Processing Units (GPGPUs)

Agent based simulation has been both a large area of study and a widely used tool for scientific research in past years…

Brandon Aaby, Kalyan Perumalla

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Exploratory Research for Extreme-Scale Science (EXPRESS)

Mon, 01 Jan 2024 00:00:00 +0000

Awards

Solicitation PDF

Original at OSTI
Cached local copy

Selected Pages

Selected Extracts

Extreme-scale science recognizes that disruptive technology changes are occurring across science applications, algorithms, computer architectures and ecosystems. Recent reports point to emerging trends and advances in high-end computing, massive datasets, visualization, and artificial intelligence on increasingly heterogeneous architectures. Significant innovation will be required in the development of effective paradigms and approaches for realizing the full potential of scientific computing from emerging technologies. Proposed research should not focus on a specific science use case, but rather on creating the body of knowledge and understanding that will inform future advances in extreme-scale science. Consequently, the funding from this FOA is not intended to incrementally extend current research in the area of the proposed project. It is expected that the proposed projects will significantly benefit from the exploration of innovative ideas or from the development of unconventional approaches.

Exploratory Research for Extreme-Scale Science (EXPRESS) opportunities exist for the following research topics:

A. Harnessing Technology Innovations to Accelerate Science through Visualization
B. Scalable Space-Time Memories for Large Discrete/Agent-Based Models
C. Neuromorphic Computing
D. Advanced Wireless
E. Quantum Hardware Emulation

Applications submitted in response to this FOA must substantially address one among the preceding list of research topics.

Digital-Twin Capabilities for Science Network Infrastructures (SBIR)

Sat, 01 Jul 2023 00:00:00 +0000

Solicitation PDF

Original at OSTI
Cached local copy

Selected Pages

Selected Extracts

Digital twins are an emerging area of modern science where a physical object (i.e., device, process, or infrastructure) is paired with a digital (virtual) version of that same object. Operations of the physical object can generate data to validate the virtual objects behavior while the virtual object allows rapid exploration of input parameters that might damage the physical object. It is this close interaction between the physical and virtual object that makes this digital-twin environment so productive.

DOE has a long history of building and operating high performance physical network infrastructures. The Energy Science Network (ESnet) supports the Office of Science lab complex and it also peers with other research and education networks (RENs) both domestically and internationally. ESnet also operates an internal 100G SDN network testbed and the NSF funded FABRIC external network testbed. Specifically:

a) The ESnet 100G Software-Defined Networking (SDN) testbed’s objective is to provide network researchers with a realistic environment for testing. The current testbed enables 100G application / middleware experiments in addition to Science DMZ and SDN control/data plane experiments.

b) FABRIC: The National Science Foundation (NSF) collaboration is building a national research infrastructure that will enable the computer science and networking community to develop and test novel architectures that could yield a faster, more secure Internet. What is missing is a virtual companion, a digital twin, to these testbeds.

This topic solicits applications that would create the network simulation capabilities that would accurately and reliably duplicate the operational and performance capabilities of these testbeds creating their digital twin.

Mixed Integer Solver Technology for Accelerated Computing Systems (SBIR)

Sat, 01 Jul 2023 00:00:00 +0000

Solicitation PDF

Original at OSTI
Cached local copy

Selected Pages

Selected Extracts

This topic is focused on specific technologies that are required to advance the state of accelerated computing applied to mixed integer programming (MIP) problems arising in scientific applications. The primary focus of this topic is on the computer science needed to address the challenges in manifestation of scalable, distributed (multi-node) algorithmic techniques and not on combinatorial theory development.

MIP problems underlie many important application areas of interest to DOE, including biological systems, transportation networks, electric grids, and user facility infrastructures. While significant advances have been made in the theory and implementation of MIP solver methods on conventional central processing unit (CPU)- based hardware, new advances are necessary to fully utilize the DOE investments in accelerated computing platforms such as graphical processing unit (GPU)-based computers and high-performance computing systems. Preference may be given to applications that leverage existing ASCR software investments.

Grant applications focused on the following will be considered out of scope:

Cut generation, cut storage, cut manipulation methods,
Column generation methods,
Theory,
Fragments of technology that are isolated and cannot be demonstrated as part of a working MIP solver on standard problems such as found in the MIPLIB series, and
Solutions that cannot be demonstrated to run on GPU-based accelerators used in current or planned supercomputing systems of DOE leadership computing facilities.

Grant applications are sought in the following subtopics:

a. Efficient Distributed Tree Management This topic is focused on tree management that arises in branch-and-bound or branch-and-cut (B&C) methods to MIP solution methods. Research must focus on efficient representation and encoding of the B&C tree on accelerated memory hierarchies and address the challenges of efficient tree node movement, including exploitation of direct memory access (DMA) of accelerated memory across high-speed networks. Methods must solve the problem of scalable and efficient manipulation of B&C tree nodes. This includes the ability to query the quality of linear program relaxation, node ancestor identification, node deletion, and updates to the node data.

b. Efficient Linear Program Relaxation Solution Implementations of interior or exterior point methods must be developed specifically optimized for accelerated hardware using single-instruction-multiple-thread (SIMT) control flows or reconfigurable field programmable gate arrays (FPGAs). Methods must build on existing or new sparse and dense solvers and capable of static or dynamic (on-the-fly) choice of sparse versus dense solver based on the density of matrices20 Return to Table of Contents encountered in the input scenarios. Applicants may propose solving the linear program relaxations of MIP problem matrices that either fit entirely within a single node’s memory or large problem sizes where matrices do not fit within a single node’s memory but span multiple node memories. Milestones must aim to solve the relaxations of root nodes in increasing fractions (10%, 50%, 75%, 90%) of the problems in the MIPLIB 2017 problem set (with priming or probing methods not necessarily applied to the root problems).

ExaSGD Performance Profiling

Tue, 28 Jun 2022 00:00:00 +0000

View the report here.

For the context for this report, please see the ExaSGD ECP Project.

Computer Science Research Needs for Parallel Discrete Event Simulation (PDES)

Wed, 11 May 2022 00:00:00 +0000

https://www.osti.gov/servlets/purl/1855247

Design Considerations for GPU-based Mixed Integer Programming on Parallel Computing Platforms

Mon, 09 Aug 2021 00:00:00 +0000

https://dl.acm.org/doi/abs/10.1145/3458744.3473366

Generating Massive Scale-free Networks: Novel Parallel Algorithms using the Preferential Attachment Model

Sat, 16 May 2020 00:00:00 +0000

https://dl.acm.org/doi/abs/10.1145/3391446

COVID-relevant Scalable Computational Research Directions and Tools

Thu, 09 Apr 2020 00:00:00 +0000

This seminar conveys some directions and technical ideas being pursued by the Discrete Computing Systems Group of the Computer Science and Mathematics Division, in collaboration with others at the lab. Some of the scalable computational tools ready for applying to challenging computational problems are presented. Actual working codes ready for customization to COVID-related efforts are described, which are built for scaling to supercomputing platforms such as Summit.

Topics that are covered include:

A high resolution simulator, ExaCorona, that scales from laptops to leadership class supercomputers, is outlined that uses a discrete event model of virus spread, with probabilistically timed state transitions at the individual level across millions of individuals represented with arbitray geography and mobility characteristics.
A clonable simulation framework, CloneX, is introduced that enables millions of “what-if” scenarios to be executed rapidly on thousands of GPUs of Summit and similar supercomputers. An SEIR-based epidemiological model is outlined for numerous what-if simulations of disease spread that can be executed for country-scale populations like India’s, with ‘what-if’ scenarios, each varying in the outbreak points (hotspots), quarantines, vaccinations and hospitalizations.
A machine learning pipeline for the prediction of material structure properties directly from their neutron scattering profiles (development as part of the ExaLearn ECP co-design project). A brief overview of this system is provided, which is being applied for studies of new therapeutic targets and viral protein-structure-assisted drug design studies related to the COVID outbreak.
Network science methods are outlined for detecting information cascades in time varying large-scale social communication networks. We discuss its implications for detecting occurrence/response or epidemic related events from Twitter and similar global interaction systems.

Energy Conservation Through Cloned Execution Of Simulations

Sun, 08 Dec 2019 00:00:00 +0000

https://ieeexplore.ieee.org/abstract/document/9004821

Exact-Differential Simulation: Differential Processing of Large-Scale Discrete Event Simulations

Tue, 18 Jun 2019 00:00:00 +0000

https://dl.acm.org/doi/abs/10.1145/3301499

Towards Native Execution of Deep Learning on a Leadership-Class HPC System

Mon, 20 May 2019 00:00:00 +0000

https://ieeexplore.ieee.org/abstract/document/8778212

Scalable Cloning on Large-Scale GPU Platforms with Application to Time-Stepped Simulations on Grids

Wed, 31 Jan 2018 00:00:00 +0000

https://dl.acm.org/doi/abs/10.1145/3158669

GPU-based parallel algorithm for generating massive scale-free networks using the preferential attachment model

Mon, 11 Dec 2017 00:00:00 +0000

https://ieeexplore.ieee.org/abstract/document/8258315

Generating Billion-Edge Scale-Free Networks in Seconds: Performance Study of a Novel GPU-based Preferential Attachment Model

Sun, 01 Oct 2017 00:00:00 +0000

https://www.osti.gov/biblio/1399438

Identifying and Harnessing Concurrency for Parallel and Distributed Network Simulation

Wed, 10 Feb 2016 00:00:00 +0000

Andelfinger’s thesis online

Discrete Event Execution with One-Sided and Two-Sided GVT Algorithms on 216,000 Processor Cores

Wed, 01 Jan 2014 00:00:00 +0000

[Pub 121]

http://tomacs.acm.org

Parallel Discrete Event Simulation

Wed, 01 Jan 2014 00:00:00 +0000

[Pub 147]

http://hpcs2014.cisedu.info/

Reverse Computation for Rollback-based Fault Tolerance in Large Parallel Systems

Wed, 01 Jan 2014 00:00:00 +0000

[Pub 119]

http://link.springer.com/article/10.1007%2Fs10586-013-0277-4

Simulating Billion-Task Parallel Programs

Wed, 01 Jan 2014 00:00:00 +0000

[Pub 143]

http://atc.udg.edu/SPECTS2014/

Towards Reversible Basic Linear Algebra Subprograms: A Performance Study

Wed, 01 Jan 2014 00:00:00 +0000

[Pub 145]

http://www.springer.com/series/8183

Virtual Machine-Based Simulation Platform For MANET-Based Cyber Infrastructure

Wed, 01 Jan 2014 00:00:00 +0000

[Pub 148]

http://www.scs.org/jdms

Simulation des Réseaux à grande Échelle sur les architectures de calcules hètèrogénes

Sun, 01 Dec 2013 00:00:00 +0000

Romdhanne’s thesis online

Interfacing JavaScript and MPI

Tue, 13 Aug 2013 00:00:00 +0000

Efficient Heterogeneous Execution on Large Multicore and Accelerator Platforms: Case Study Using a Block Tridiagonal Solver

Tue, 01 Jan 2013 00:00:00 +0000

[Pub 120]

http://www.journals.elsevier.com/journal-of-parallel-and-distributed-computing/

Improved Parallelization of the SIESTA Magneto-hydrodynamic Equilibrium Code Using Cyclic Reduction

Tue, 01 Jan 2013 00:00:00 +0000

[Pub 141]

http://www.aps.org/meetings/meeting.cfm?name=DPP13

Scaling Optimization of the SIESTA MHD Code

Sun, 01 Jan 2012 00:00:00 +0000

[Pub 142]

http://www.aps.org/meetings/meeting.cfm?name=DPP12

Towards Highly Interactive, GPU-based Evaluation of Evacuation Transport Scenarios at State-Scale

Sun, 01 Jan 2012 00:00:00 +0000

[Pub 111]

http://sim.sagepub.com/content/88/6/746

Improved Parallelization of the SIESTA Magneto-hydrodynamic Equilibrium Code Using Cyclic Reduction

Sat, 01 Jan 2011 00:00:00 +0000

[Pub 128]

http://www.aps.org/meetings/meeting.cfm?name=DPP11

Improving Multi-Million Virtual Rank MPI Execution in MUPI

Sat, 01 Jan 2011 00:00:00 +0000

[Pub 131]

http://pdcc.ntu.edu.sg/mascots2011/

Towards High Performance Discrete Event Simulations of Smart Electric Grids

Sat, 01 Jan 2011 00:00:00 +0000

[Pub 130]

An Incremental Parallelization Approach Applied to the ORNL/NRC FAVOR Code

Fri, 01 Jan 2010 00:00:00 +0000

[Pub 124]

www.osti.gov

Efficient Simulation of Agent-Based Models on Multi-GPU and Multi-Core Clusters

Fri, 01 Jan 2010 00:00:00 +0000

[Pub 109]

http://www.simutools.org

A Case Study of the Performance of Speculative Asynchronous Simulation on Parallel Computers

Mon, 01 Jan 2007 00:00:00 +0000

[Pub 139]

http://science.energy.gov/wdts/

Integrated Analysis of Environment-Driven Operational Effects in Sensor Networks

Sun, 01 Jan 2006 00:00:00 +0000

[Pub 70]

Network Simulation

Sun, 01 Jan 2006 00:00:00 +0000

[Pub 3]

http://www.morganclaypool.com/toc/cnt/1/1

On Evaluation Needs of Real-life Sensor Network Deployments

Sun, 01 Jan 2006 00:00:00 +0000

[Pub 18]

Virtual Simulator: An Infrastructure for Design and Performance-Prediction of Massively Parallel Codes

Sat, 01 Jan 2005 00:00:00 +0000

[Pub 105]

A Federated Approach to Distributed Network Simulation

Thu, 01 Jan 2004 00:00:00 +0000

[Pub 12]

Conservative Synchronization of Large-scale Network Simulations

Thu, 01 Jan 2004 00:00:00 +0000

[Pub 43]

Large-Scale Network Simulation - How Big? How Fast?

Wed, 01 Jan 2003 00:00:00 +0000

[Pub 44]

Scalable RTI-based Parallel Simulation of Networks

Wed, 01 Jan 2003 00:00:00 +0000

[Pub 46]

HPC | Kalyan Perumalla

Exascale Computing for the National Energy Grid

Overview

The Problem

The Solution

Organization

Gallery

Related Publications

ReveR-SES: Reversible Software Execution Systems

Overview

Scope

Primary Scientific Thrusts

Science Impacts

Gallery

Organization

Selected Publications

Network Simulation

Overview

Reference

Intelligent Design of Structure for Function

Overview

Organization

Gallery

BLOCKTRI: Parallel Block Tridiagonal Solver

Organization

Selected Publications

NetWarp

Organization

Gallery

Related Publications

Rocks3D-HPC

Organization

Gallery

MutEnt

Overview

Organization

Related Publications

Gallery

RealSim: Real-Time Simulations

Gallery

Organization

Related Publications

Exploratory Research for Extreme-Scale Science (EXPRESS)

Awards

Solicitation PDF

Selected Pages

Selected Extracts

Digital-Twin Capabilities for Science Network Infrastructures (SBIR)

Solicitation PDF

Selected Pages

Selected Extracts

Mixed Integer Solver Technology for Accelerated Computing Systems (SBIR)

Solicitation PDF

Selected Pages

Selected Extracts

ExaSGD Performance Profiling

Computer Science Research Needs for Parallel Discrete Event Simulation (PDES)

Design Considerations for GPU-based Mixed Integer Programming on Parallel Computing Platforms

Generating Massive Scale-free Networks: Novel Parallel Algorithms using the Preferential Attachment Model

COVID-relevant Scalable Computational Research Directions and Tools

Energy Conservation Through Cloned Execution Of Simulations

Exact-Differential Simulation: Differential Processing of Large-Scale Discrete Event Simulations

Towards Native Execution of Deep Learning on a Leadership-Class HPC System

Scalable Cloning on Large-Scale GPU Platforms with Application to Time-Stepped Simulations on Grids

GPU-based parallel algorithm for generating massive scale-free networks using the preferential attachment model

Generating Billion-Edge Scale-Free Networks in Seconds: Performance Study of a Novel GPU-based Preferential Attachment Model

Identifying and Harnessing Concurrency for Parallel and Distributed Network Simulation

Discrete Event Execution with One-Sided and Two-Sided GVT Algorithms on 216,000 Processor Cores

Parallel Discrete Event Simulation

Reverse Computation for Rollback-based Fault Tolerance in Large Parallel Systems

Simulating Billion-Task Parallel Programs

Towards Reversible Basic Linear Algebra Subprograms: A Performance Study

Virtual Machine-Based Simulation Platform For MANET-Based Cyber Infrastructure

Simulation des Réseaux à grande Échelle sur les architectures de calcules hètèrogénes

Interfacing JavaScript and MPI

Efficient Heterogeneous Execution on Large Multicore and Accelerator Platforms: Case Study Using a Block Tridiagonal Solver

Improved Parallelization of the SIESTA Magneto-hydrodynamic Equilibrium Code Using Cyclic Reduction

Scaling Optimization of the SIESTA MHD Code

Towards Highly Interactive, GPU-based Evaluation of Evacuation Transport Scenarios at State-Scale

Improved Parallelization of the SIESTA Magneto-hydrodynamic Equilibrium Code Using Cyclic Reduction