Research Posters Display
2021-11-17 08:30 - 17:00 (America/Chicago) | Second Floor Atrium
Posters, Research Posters

Parallel Framework for Updating Large-Scale Dynamic Networks

Srinivasan, Pandey, Khanda, Srinivasan, Das

Analysis of large-scale dynamic networks is vital for understanding the relationship between entities that constantly change over time. Unfortunately, existing algorithms for identifying graph properties are optimized for static networks and resort to recomputing those properties over the entire net...

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Feature Reduction of Darshan Counters Using Evolutionary Algorithms

Rajesh, Koziol, Byna, Tang, Bez...

Feature reduction is an integral part of data preparation in machine learning. It helps denoise the data and makes it easier to fit the model. Predicting the performance of an application using Darshan counters can be tricky due to the large amount of data available, with not all of them being perti...

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GASNet-EX Memory Kinds: Support for Device Memory in PGAS Programming Models

Hargrove, Bonachea, MacLean, Waters

There is an emerging need for adaptive, lightweight communication in irregular HPC applications at exascale, where GPU accelerators provide the majority of available compute cycles. To address this need, Lawrence Berkeley National Lab is developing a programming system to support distributed-memory...

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Handling C++ Exceptions in MPI Applications

Jaros

Handling error states in C++ applications is managed by exceptions. In distributed applications, it is necessary to inform the other processes, that something wrong happened, and the application should either recover from the faulty state, or report the error and terminate gracefully. Unfortunately,...

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Fargraph: Optimizing Graph Workload on RDMA-Based Far Memory Architecture

Wang, Li, Wang, Zhang, Wang...

Disaggregated architecture brings new opportunities to memory-consuming applications like graph analytics. It allows one to outspread memory access pressure from local to far memory, providing an attractive alternative to disk-based processing. In this paper, we take the first step to analyze the im...

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Analyzing Complex Memory Systems

Butcher

Several recent systems in the Top500 include many-core chips with complex memory systems, including multiple memory channels. Many many-core chips feature an intermediate layer of memory with higher bandwidth and lower capacity then main memory. Intermediate memory exists either in a cache or a sepa...

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Detecting Network Intrusion Anomalies through Egonet-Based Data Mining with Apache Spark

Paik, Kwak, Lu

Network intrusions often contain dangerous breaches to network security systems and their data. We design an anomaly detection system to identify network intrusions. Our proposed detection method is inspired by the use of egonets in the oddball algorithm but differs by the extracted features and the...

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HyperQueue: Overcoming Limitations of HPC Job Managers

Böhm, Beránek, Cima, Macháček, Jha...

In recent years, HPC workloads and communities have undergone substantial paradigm shifts. There is an increasing amount of users that want to leverage HPC clusters to execute many simple and embarrassingly parallel tasks as easily as possible. Due to the limitations of traditional HPC job managers,...

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An Interactive GPU Metric Dashboard for HPC clusters

Shi, Cook, Chatterjee, Blaschke

Scaling up programs to run at the scale of a modern high-performance computing (HPC) center can be a daunting task. One of the first questions developers ask is: “Is my program using all the hardware available?” Many tools can extract detailed performance data on applications. But the level of detai...

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Multiple Same Level and Telescoping Nesting in GFDL’s FV3

Mouallem, Benson, Harris

The current two-way, single nest capability in the FV3 dynamical core, used in weather and climate applications by a diverse group of institutions and organizations, is upgraded with the capability to employ multiple same-level nests as well as telescope, or embed, the various nests within each othe...

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Heterogeneous Computing for Undergraduates: A Module-Driven Approach

Qasem, Bunde, Schielke

To achieve aggressive performance and power goals, HPC systems are becoming increasingly heterogeneous. This represents an educational challenge since few current curricula include much about heterogeneous computing except possibly in upper-division electives. This poster presents a set of modules...

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Towards a Scalable and Distributed High-Performance SHAD C++ library

Wu, Castellana, Kaiser

SHAD is the Scalable High-performance Algorithms and Data-structures C++ library, providing general purpose building blocks and supporting high-level custom utilities. SHAD is designed with scalability, flexibility, productivity and portability in mind, and serves as a playground for research in par...

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Chaining Multiple Tools and Libraries Using Gotcha

Xu, Mohror, Devarajan, Stanavige, Bhatele

In HPC, it is common to use tools to understand the performance of applications. Users often want to run applications linked with multiple performance tools to complement each other, as tools may record different information. Many tools operate by intercepting application function calls with "wrappe...

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Learning-Based Content Delivery in 5G-Enabled Multi-Access Edge Computing

Farhangi Maleki, Ma, Mashayekhy, La Roche

The demand for content such as multimedia services with high performance (e.g., ultra-low latency) requirements has increased significantly, posing heavy backhaul congestion in mobile networks. The integration of multi-access edge computing (MEC) and 5G network is an emerging solution that alleviate...

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Accurate Throughput Prediction of Basic Blocks on Recent Intel Microarchitectures

Abel, Reineke

Tools to predict the throughput of basic blocks on a specific microarchitecture are useful to optimize software performance and to build optimizing compilers. In recent work, several such tools have been proposed. The accuracy of their predictions, however, has been shown to be relatively low. To a ...

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RIKEN CGRA: Data-Driven Architecture as an Extension of Multicore CPU for Future HPC

Adhi, Kojima, Tan, Podobas, Sano

A coarse-grained reconfigurable array (CGRA) is currently gaining momentum to enter the HPC market as deep-learning accelerators due to its potential for performance scalability and energy efficiency. Traditionally, the usage of CGRA was limited in embedded systems to provide extra computing perform...

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SODA-OPT: System-Level Design in MLIR for HLS

Bohm Agostini, Kaeli, Tumeo

High-level-synthesis (HLS) enables the generation of hardware descriptions from applications implemented with high-level languages. State-of-the-art tools, however, typically require the application to be manually translated to C/C++ and carefully annotated to improve final design performance. This...

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Support in OpenMP for Multi-GPU Parallelism

Torres, Kale, Malik, Scogland, Ferrer...

Nodes of emerging supercomputers have multiple GPUs, i.e., a multi-GPU, on them. Applications are often parallelized across the GPUs of a multi-GPU using MPI, but a more performant and portable solution for parallelizing across the GPUs is needed. OpenMP, which is used to parallelize computation wit...

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Performance Analysis of Containerized OrangeFS in HPC Environment

Yildirim, Tang, Kougkas, Sun

Containerization is on the rise in cloud computing due to its benefits in reproducibility, portability and lightweight properties. The need for scalable and reproducible products and the necessity to interoperate on everything from local machines to large-scale HPC resources have made HPC solutions ...

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Breadth-First Search on Xilinx Versal

Prado Alves, Minutoli, Belviranli, Tumeo

The new Xilinx Versal Platform provides a highly heterogeneous system to programmers. How these diverse resources can be utilized effectively is an open question. This project implements breadth-first search (BFS) on this platform, utilizing all available regions to accelerate this workload. This is...

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Towards an Efficient Parallel Skeleton for Generic Iterative Stencil Computations in Distributed GPUs

de Castro, Santamaria-Valenzuela, Miguel-López, Torres, Gonzalez-Escribano

Iterative stencil applications present a high degree of parallelism. The approach is appropriate for modern many-core systems, like GPUs. The huge arrays needed in many real problems, however, require multiple-GPUs memory. Manually programming multi-GPU solutions is complex, involving synchronizatio...

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Flexible GMRES with Analog Accelerators

Gupta, Kalantzis, Squillante, Wu, Avron...

This research poster describes advances in the solution of general sparse linear systems by applying the preconditioning step primarily through the help of an analog crossbar array. These architectures can achieve high degrees of parallelism with low energy consumption by mapping matrices onto array...

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Enabling Combustion Science Simulations for Future Exascale Machines

Rood, Henry de Frahan, Day, Sitaraman, Yellapantula...

Reacting flow simulations for combustion applications require extensive computing capabilities. Leveraging the AMReX library, the Pele suite of combustion simulation tools targets the largest supercomputers available and future exascale machines. We introduce PeleC, the compressible solver in the Pe...

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Capturing Relationships Based on Structure Similarity for Self-Describing Scientific Data Formats

Niu, Zhang, Byna, Chen

Many scientific data sets use self-describing files for storing data, and files within a data set are often isolated without any definition of relationships among them. Because of the isolated management of scientific data files, locating, assimilating and utilizing relationships for a given query r...

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Core-Idling on MPI Intra-Node Communication Channels for Energy Efficiency

Kim, Jin, Byun

Busy-waiting used to implement parallel programming models can provide low latency but at the expense of energy. There have been several studies to enhance the energy efficiency of MPI libraries and applications by lowering the CPU speed during busy-waiting or turning off CPU components. While most ...

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Optimizing and Extending the Functionality of EXARL for Scalable Reinforcement Learning

Chenna, Cosburn, Ezeobi, Moraru, Lim...

Easily eXtendable Architecture for Reinforcement Learning (EXARL) is a scalable reinforcement learning framework, part of the Exascale Computing Project (ECP) funded ExaLearn program, designed to facilitate reinforcement learning (RL) research for complex scientific environments. In RL, agents are a...

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A Fast Parameter-Free Preconditioner for Structured Grid Problems

kumar, aggarwal, Kakkar

A fast, robust, parallel and parameter-free version of a frequency-filtering preconditioner is proposed for linear systems corresponding to the diffusion equation on a structured grid. Proposed solver is faster than the state-of-the-art solvers.

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Monitoring Urban Changes with Ensemble of Neural Networks and Deep-Temporal Remote Sensing Data

Zitzlsberger, Podhoranyi, Svatoň, Lazecký, Martinovič

Urban change detection with remote sensing data covers a wide field of applications like understanding socio-economic impacts, identifying new settlements, or analyzing trends of urban sprawl. It is used for decades. Analyses, however, are usually carried out manually by selecting high-quality sampl...

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Similarity Measurement for Proxy Application Fidelity

Chen, Aaziz, Cook, Wildani

Proxy applications, designed to represent similar but much larger and more complex parent applications, are widely used for system co-design and procurement. Quantitative validation, however, to prove that proxies are faithful representations of their parents, is missing. In this work, we apply seve...

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HDF5 VOL Connector to Apache Arrow

Ye, Kougkas, Sun

Apache Arrow is widely used in Big Data Analysis and Cloud Computing Area because of its standardized in-memory column format. It is a columnar, in-memory data representation that enables analytical systems and data sources to exchange and process data in real-time. It could create an in-memory colu...

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Fusion Research Using Azure A100 HPC instances

Sfiligoi, Candy, Subramanian

Fusion simulations have in the past required the use of leadership scale HPC resources to produce advances in physics. One such package is CGYRO, a premier multi-scale plasma turbulence simulation code. CGYRO is a typical HPC application that would not fit into a single node, as it requires O(100 GB...

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Accelerating the Visualization of Spatio-Temporal Simulations with Non-Evolving Meshes

Ribes, Geay, Westphal

Numerical simulations, such as finite elements, deal with both space and time discretizations of fields. For the discretization of space, a mesh is normally used. Concerning the temporal evolution of the spatial discretization, in the general case, a different mesh can be used per time step. It is o...

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Padding to Extend the Bruck Algorithm for Non-Uniform All-to-All Communication

Fan, Gilray, Kumar

The latency of the standard MPI_Alltoallv implementations is linear in the number of processes. Such linear complexity performs poorly when applications are deployed on millions of cores for short messages, which is dominated by latency. Bruck's algorithm is a classic logarithm algorithm for uniform...

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Detecting and Identifying Applications by Job Signatures

Li, Cook, Chen

Knowing the applications of jobs running in high-performance computing (HPC) systems is invaluable for administrators. This research aims to detect and identify applications through job signatures built upon monitoring traces obtained from the LDMS monitoring infrastructure on Cori. By constructing ...

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Utilizing Persistent Memory in Parallel I/O Libraries

Logan, Lofstead, Levy, Widener, Sun...

Scientific applications use parallel I/O (PIO) libraries to manage the complexity of I/O to distributed storage efficiently. PIO libraries, however, have not adequately adapted to the emergence of persistent memory (PMEM), which provides comparable performance to DRAM. They interact with PMEM using ...

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FPGA-Accelerated Ripples

Neff, Minutoli, Tumeo, Becchi

Influence Maximization is an important graph algorithm that is gaining traction in areas where social networks and other related graphs are processed and analyzed. The long runtime of the algorithm opened the door for optimizations, but is challenging to parallelize and port onto novel architecture ...

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Hashed-Coordinate Storage of Sparse Tensors

Lowe, Charles, Singh

Tensors, or n-way arrays, are becoming increasingly important in many fields. In recent applications, tensors are extremely sparse and have such a high degree that dense storage becomes intractable. To address this, several sparse storage formats have been proposed, with most formats being some vari...

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Towards Optimal Graph Coloring Using Rydberg Atoms

Vitali, Viviani, Vercellino, Scarabosio, Scionti...

Quantum mechanics is expected to revolutionize the computing landscape in the near future. Among the many candidate technologies for building universal quantum computers, Rydberg atoms-based systems stand out for being capable of performing both quantum simulations and working as gate-based univers...

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Parallel GRB Source Localization Pipelines for the Advanced Particle-Astrophysics Telescope

Sudvarg, Wheelock, Buhler, Buckley, Chen

The Advanced Particle-astrophysics Telescope (APT) is a planned space-based observatory to survey the entire sky for gamma-ray bursts (GRBs). It seeks to promptly detect these transient events, then communicate with narrow-band instruments for follow-up observations. To this end, we are developing a...

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Hardware Acceleration of Complex Machine Learning Models through Modern High-Level Synthesis

Curzel, Tumeo, Ferrandi

Machine learning algorithms continue to receive significant attention from industry and research. As the models increase in complexity and accuracy, their computational and memory demands also grow, pushing for more powerful, heterogeneous architectures; custom FPGA/ASIC accelerators are often the b...

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Code Generation and Optimization for Deep-Learning Computations on GPUs via Multi-Dimensional Homomorphisms

Schulze, Rasch, Gorlatch

We present our work-in-progress code generation and optimization approach for DL computations based on the algebraic formalism of multi-dimensional homomorphisms (MDH). We show that popular DL computations can be expressed in the MDH formalism, thereby exploiting the already existing MDH GPU code ge...

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Accelerating Parallel Monte Carlo Simulations for Statistical Physics: Portability on Many-Core Processors

Sattar, Li

Monte Carlo (MC) simulations are important tools for studying thermodynamics and materials properties at finite temperature. Scaling up to larger systems allows for simulations comparable to experimental length scale. In this work, we focus on improving the weak scaling performance to simulate large...

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Open-Source High-Performance Computing for Applications in Engineering: DEM, SPH and Multi-Agent Vehicle Simulations with Project Chrono

Zhang, Hu, Benatti, Fang, Zhou...

This poster touches on three HPC-related research thrusts based on Project Chrono. Chrono::GPU and Chrono::FSI leverage GPU computing to accelerate large-scale granular dynamic simulations (based on DEM and SPH respectively), while SynChrono exploits MPI to support real time multi-agent autonomous v...

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