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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records

CSU Final Report on the Math/CS Institute CACHE: Communication-Avoiding and Communication-Hiding at the Extreme Scale

The CACHE project entails researching and developing new versions of numerical algorithms that result in data reuse that can be scheduled in a communication avoiding way. Since memory accesses take more time than any computation and require the most power, the focus on turning data reuse into data locality is critical to improving performance and reducing power usage in scientific simulations. This final report summarizes the accomplishments at Colorado State University as part of the CACHE project.

97 MATHEMATICS AND COMPUTING↗

Automatic translation of MPI source into a latency-tolerant, data-driven form

Hiding communication behind useful computation is an important performance programming technique but remains an inscrutable programming exercise even for the expert. We present Bamboo, a code transformation framework that can realize communication overlap in applications written in MPI without the need to intrusively modify the source code. Bamboo reformulates MPI source into the form of a task dependency graph that expresses a partial ordering among tasks, enabling the program to execute in a data-driven fashion under the control of an external runtime system. Experimental results demonstrate that Bamboo significantly reduces communication delays while requiring only modest amounts of programmer annotation for a variety of applications and platforms, including those employing co-processors and accelerators. Moreover, Bamboo's performance meets or exceeds that of labor-intensive hand coding. The translator is more than a means of hiding communication costs automatically; it demonstrates the utility of semantic level optimization against a wellknown library.

Communication-computation↗

Performance analysis of distributed symmetric sparse matrix vector multiplication algorithm for multi-core architectures

In this article, sparse matrix vector multiply (SpMVM) is an important kernel that frequently arises in high performance computing applications. Due to its low arithmetic intensity, several approaches have been proposed in literature to improve its scalability and efficiency in large scale computations. In this paper, our target systems are high end multi-core architectures and we use messaging passing interface + open multiprocessing hybrid programming model for parallelism. We analyze the performance of recently proposed implementation of the distributed symmetric SpMVM, originally developed for large sparse symmetric matrices arising in ab initio nuclear structure calculations. We also study important features of this implementation and compare with previously reported implementations that do not exploit underlying symmetry. Our SpMVM implementations leverage the hybrid paradigm to efficiently overlap expensive communications with computations. Our main comparison criterion is the "CPU core hours" metric, which is the main measure of resource usage on supercomputers. We analyze the effects of topology-aware mapping heuristic using simplified network load model. Furthermore, we have tested the different SpMVM implementations on two large clusters with 3D Torus and Dragonfly topology. Our results show that the distributed SpMVM implementation that exploits matrix symmetry and hides communication yields the best value for the "CPU core hours" metric and significantly reduces data movement overheads.

97 MATHEMATICS AND COMPUTING↗

Asynchronous communication in spectral-element and discontinuous Galerkin methods for atmospheric dynamics – a case study using the High-Order Methods Modeling Environment (HOMME-homme_dg_branch)

The scalability of computational applications on current and next-generation supercomputers is increasingly limited by the cost of inter-process communication. We implement non-blocking asynchronous communication in the High-Order Methods Modeling Environment for the time integration of the hydrostatic fluid equations using both the spectral-element and discontinuous Galerkin methods. This allows the overlap of computation with communication, effectively hiding some of the costs of communication. A novel detail about our approach is that it provides some data movement to be performed during the asynchronous communication even in the absence of other computations. This method produces significant performance and scalability gains in large-scale simulations.

58 GEOSCIENCES↗

Multi-GPU Implementation of a 3D Finite Difference Time Domain Earthquake Code on Heterogeneous Supercomputers

We have developed a highly scalable 3D Finite Difference GPU code for use in earthquake engineering and disaster management through regional petascale earthquake simulations. This MPI-CUDA code is based on a widely-used wave propagation code called AWP-ODC and restructured for high throughput and efficiency on a heterogeneous computing architecture. We present an effective communication reduction technique for leveraging GPUs with minimal PCI-e overhead, and a novel overlapping method to fully hide data communication latency between GPUs. The optimization concept used in this work can be extended to general stencil computing on a structured grid. The benchmarks demonstrated sustained 100 TFlops in single precision for 49 billion mesh points using 952 GPUs on the NCCS Titan Phase 5 system, which is a 77-fold speedup compared to the CPU version of the code. This multi-GPU implementation has been validated and used for a large-scale verification wave propagation simulation of Mw5.4 Chino Hills earthquake using 128 GPUs.

58 GEOSCIENCES↗

On Eliminating Synchronous Communication in Molecular Simulations to Improve Scalability

Molecular dynamics simulation, as a complementary tool to experimentation, has become an important methodology for the understanding and design of molecular systems as it provides access to properties that are difficult, impossible or prohibitively expensive to obtain experimentally. Many of the available software packages have been parallelized to take advantage of modern massively concurrent processing resources. The challenge in achieving parallel efficiency is commonly attributed to the fact that molecular dynamics algorithms are communication intensive. This paper illustrates how an appropriately chosen data distribution and asynchronous one-sided communication approach can be used to effectively deal with the data movement within the Global Arrays/ARMCI programming model framework. A new put_notify capability is presented here, allowing the implementation of the molecular dynamics algorithm without any explicit global or local synchronization or global data reduction operations. In addition, this push-data model is shown to very effectively allow hiding data communication behind computation. Rather than data movement or explicit global reductions, the implicit synchronization of the algorithm becomes the primary challenge for scalability. Without any explicit synchronous operations, the scalability of molecular simulations is shown to depend only on the ability to evenly balance computational load.

Straatsma, TP↗

HipBone: A performance-portable graphics processing unit-accelerated C++ version of the NekBone benchmark

We present hipBone, an open-source performance-portable proxy application for the Nek5000 (and NekRS) computational fluid dynamics applications. HipBone is a fully GPU-accelerated C++ implementation of the original NekBone CPU proxy application with several novel algorithmic and implementation improvements which optimize its performance on modern fine-grain parallel GPU accelerators. Our optimizations include a conversion to store the degrees of freedom of the problem in assembled form in order to reduce the amount of data moved during the main iteration and a portable implementation of the main Poisson operator kernel. We demonstrate near-roofline performance of the operator kernel on three different modern GPU accelerators from two different vendors. We present a novel algorithm for splitting the application of the Poisson operator on GPUs which aggressively hides MPI communication required for both halo exchange and assembly. Our implementation of nearest-neighbor MPI communication then leverages several different routing algorithms and GPU-Direct RDMA capabilities, when available, which improves scalability of the benchmark. We demonstrate the performance of hipBone on three different clusters housed at Oak Ridge National Laboratory, namely, the Summit supercomputer and the Frontier early-access clusters, Spock and Crusher. Our tests demonstrate both portability across different clusters and very good scaling efficiency, especially on large problems.

Computer Science↗

Automatic Transformation of MPI Programs to Asynchronous, Graph-Driven Form

The goals of this project are to develop new, scalable, high-fidelity algorithms for atomic-level simulations and program transformations that automatically restructure existing applications, enabling them to scale forward to Petascale systems and beyond. The techniques enable legacy MPI application code to exploit greater parallelism though increased latency hiding and improved workload assignment. The techniques were successfully demonstrated on high-end scalable systems located at DOE laboratories. Besides the automatic MPI program transformations efforts, the project also developed several new scalable algorithms for ab-initio molecular dynamics, including new massively parallel algorithms for hybrid DFT and new parallel in time algorithms for molecular dynamics and ab-initio molecular dynamics. These algorithms were shown to scale to very large number of cores, and they were designed to work in the latency hiding framework developed in this project. The effectiveness of the developments was enhanced by the direct application to real grand challenge simulation problems covering a wide range of technologically important applications, time scales and accuracies. These included the simulation of the electronic structure of mineral/fluid interfaces, the very accurate simulation of chemical reactions in microsolvated environments, and the simulation of chemical behavior in very large enzyme reactions.

97 MATHEMATICS AND COMPUTING↗

CPSW: Common Platform Software

The “Common Platform Software” is a package which facilitates communication with common platform firmware. It is intended to provide basic access to firmware features while hiding details of the communication protocols involved. CPSW implements abstractions for entities like registers and devices and hides low-level details such as addressing or routing information, byte-order etc.

Vasquez, Jesus↗

Asynchronous I/O VOL Connector (AsyncVOL) v0.1

Asynchronous I/O is becoming increasingly popular with the large amount of data access required by scientific applications. They can take advantage of an asynchronous interface by scheduling I/O as early as possible and overlap computation or communication with I/O operations, which hides the cost associated with I/O and improves the overall performance.

Tang, Houjun↗

Accelerating Flash-X Simulations with Asynchronous I/O

Most high-fidelity physics simulation codes, such as Flash-X, need to save intermediate results (checkpoint files) to restart or gain insights into the evolution of the simulation. These simulation codes save such intermediate files synchronously, where computation is stalled while the data is written to storage. Depending on the problem size and computational requirements, this file write time can be a substantial portion of the total simulation time. In order to hide the I/O latency of checkpointing, asynchronous I/O methods have been introduced. These methods use background threads for performing I/O while the main threads continue with the simulation. The usage of background threads can compete for resources on the node as well as with communication. In this paper, we evaluate the overheads and the overall benefit of asynchronous I/O in HDF5 to simulations. Results from real-world high-fidelity simulations on the Summit supercomputer show that I/O operation is overlapped with application communication or computation or both, effectively hiding some or all of the I/O latency. Our evaluation shows that while using asynchronous I/O adds overhead to the application, the I/O time reduction is more significant, resulting in overall up to 1.5X performance speedup.

Jain, Rajeev↗

mochi-hpc/mochi-margo

Margo provides Argobots-aware bindings to the Mercury RPC library. Margo combines Mercury and Argobots to simplify development of distributed services. Mercury operations are presented as conventional blocking operations, and RPC handlers are presented as sequential threads. This configuration enables high degree of concurrency while hiding the complexity associated with asynchronous communication progress and callback management.

Carns, Phil↗

Hiding Critical Targets in Smart Grid Networks

With the integration of advanced communication technologies, the power grid is expected to greatly enhance efficiency and reliability of future power systems. However, since most electrical devices in power grid substations are connected via communication networks, cyber security of these communication networks becomes a critical issue. Real-World incidents such as Stuxnet have shown the feasibility of compromising a device in the power grid network to further launch more sophisticated attacks. To deal with security attacks of this spirit, this paper aims to hide critical targets from compromised internal nodes and hence protect them from further attacks launched by those compromised nodes. In particular, we consider substation networks and propose to add carefully-controlled dummy traffic to a substation network to make critical target nodes indistinguishable from other nodes in network traffic patterns. This paper describes the design and evaluation of such a scheme. Evaluations show that the scheme can effectively protect critical nodes with acceptable communication cost.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Inherent secure communications using lattice based waveform design

The wireless communications channel is innately insecure due to the broadcast nature of the electromagnetic medium. Many techniques have been developed and implemented in order to combat insecurities and ensure the privacy of transmitted messages. Traditional methods include encrypting the data via cryptographic methods, hiding the data in the noise floor as in wideband communications, or nulling the signal in the spatial direction of the adversary using array processing techniques. This work analyzes the design of signaling constellations, i.e. modulation formats, to combat eavesdroppers from correctly decoding transmitted messages. It has been shown that in certain channel models the ability of an adversary to decode the transmitted messages can be degraded by a clever signaling constellation based on lattice theory. This work attempts to optimize certain lattice parameters in order to maximize the security of the data transmission. These techniques are of interest because they are orthogonal to, and can be used in conjunction with, traditional security techniques to create a more secure communication channel.

97 MATHEMATICS AND COMPUTING↗

Compressed basis GMRES on high-performance graphics processing units

Krylov methods provide a fast and highly parallel numerical tool for the iterative solution of many large-scale sparse linear systems. To a large extent, the performance of practical realizations of these methods is constrained by the communication bandwidth in current computer architectures, motivating the investigation of sophisticated techniques to avoid, reduce, and/or hide the message-passing costs (in distributed platforms) and the memory accesses (in all architectures). This article leverages Ginkgo’s memory accessor in order to integrate a communication-reduction strategy into the (Krylov) GMRES solver that decouples the storage format (i.e., the data representation in memory) of the orthogonal basis from the arithmetic precision that is employed during the operations with that basis. Given that the execution time of the GMRES solver is largely determined by the memory accesses, the cost of the datatype transforms can be mostly hidden, resulting in the acceleration of the iterative step via a decrease in the volume of bits being retrieved from memory. Together with the special properties of the orthonormal basis (whose elements are all bounded by 1), this paves the road toward the aggressive customization of the storage format, which includes some floating-point as well as fixed-point formats with mild impact on the convergence of the iterative process. We develop a high-performance implementation of the “compressed basis GMRES” solver in the Ginkgo sparse linear algebra library using a large set of test problems from the SuiteSparse Matrix Collection. We demonstrate robustness and performance advantages on a modern NVIDIA V100 graphics processing unit (GPU) of up to 50% over the standard GMRES solver that stores all data in IEEE double-precision.

97 MATHEMATICS AND COMPUTING↗

CORE-BFS: Communication-Optimized REctangular-partitioned BFS Achieving 160.845 TeraTEPS on Frontier Supercomputer

Distributed Breadth-First Search (BFS) is fundamental to many large-scale graph applications, but its performance on parallel systems is often limited by high communication overhead. This paper presents CORE-BFS, an extremely scalable GPU-based BFS implementation that introduces a unique rectangular 2D partitioning-based design for Frontier supercomputer. To further improve performance, we propose four key optimizations: (1) Rectangular 2D-partition specific data formats that use two compressed row and one compressed column status array bitmaps combined with a Double Compressed Sparse Row (DCSR) format per partition, reducing memory footprint and inter-rank traffic; (2) Adaptive frontier & communication strategy that unifies top-down and bottom-up traversal on the rectangular layout, uses lazy synchronization in top-down levels, and switches variants based on frontier size to minimize communication overhead; (3) Frontier-split degree-aware update that maps frontier vertices to thread-centric, wavefront-centric, and block-centric kernels based on their degree to improve GPU utilization and memory coalescing; (4) Row-reduction pipeline that overlaps bottom-up adjacency list processing with row-wise bitmap reduction to hide inter-rank latency. Together, these techniques increase parallelism while reducing memory and communication overhead. On the Graph500 benchmark, CORE - BFS scales up to 9,248 Frontier nodes with scale-42 graphs and reaches 160.845 TTEPS, delivering a 5.42 × speedup over our previous Frontier implementation.

Yang, Haoshen [Rutgers University]↗

HIDES: Hybrid Intrusion Detector for Energy Systems

The establishment of a resilient electric grid accompanied by a secure communications network is an ongoing battle as advanced persistent threats continue to exploit existing vulnerabilities in legacy supervisory control and data acquisition system (SCADA) infrastructure. Traditional intrusion detection systems (IDSs) lack consistent performance because of the continuously evolving attack surface of SCADA systems. These shortcomings can be overcome by integrating logical system behavior, protocol-specific knowledge, and data-based learning to develop a comprehensive IDS solution. In this paper, we present a Hybrid Intrusion Detector for Energy Systems by integrating a network-based IDS, state-of-the-art machine learning-based IDS, and model-based IDS to detect unknown and stealthy cyberattacks targeting the SCADA networks. The proposed IDS uses synchrophasor measurements and cyber logs to learn patterns of different scenarios based on spatiotemporal behaviors of power systems. As a proof of concept, we implement and validate the proposed IDS by leveraging resources available at the National Renewable Energy Laboratory's Energy Systems Integration Facility test bed. Experimental results show promising performance in detecting cyberattacks while providing realtime visualization of power system measurements and cyber logs.

machine-learning intrusion detection system↗