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At least 127 records · Page 7

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DOE OSTI2018

On Data Transfers Over Wide-Area Dedicated Connections

Dedicated wide-area network connections are employed in big data and high-performance computing scenarios, since the absence of cross-traffic promises to make it easier to analyze and optimize data transfers over them. However, nonlinear transport dynamics and end-system complexity due to multi-core hosts and distributed file systems make these tasks surprisingly challenging. We present an overview of methods to analyze memory and disk file transfers using extensive measurements over 10 Gbps physical and emulated connections with 0–366 ms round trip times (RTTs). For memory transfers, we derive performance profiles of TCP and UDT throughput as a function of RTT, which show concave regions in contrast to entirely convex regions predicted by previous models. These highly desirable concave regions can be expanded by utilizing large buffers and more parallel flows. We also present Poincar´e maps and Lyapunov exponents of TCP and UDT throughputtraces that indicate complex throughput dynamics. For disk file transfers, we show that throughput can be optimized using a combination of parallel I/O and network threads under direct I/O mode. Our initial throughput measurements of Lustre filesystems mounted over long-haul connections using LNet routers show convex profiles indicative of I/O limits.

Rao, Nageswara S.↗

DOE OSTI2021

Scalable augmented enumeration and metadata operations for large filesystems

Systems, apparatus, and methods are disclosed for performing scalable operations in a file system. Metadata entries in a namespace or directory tree are sharded across multiple file metadata servers. An augmented enumeration operation, such as listing a directory, is parallelized across the multiple file metadata servers, transparently to clients. Exemplary augmentation features can include filtering and sorting. Augmentation features can be executed concurrently with enumeration, prior to enumeration, after enumeration, or as a combination of these, and can utilize pre-built index structures or holding structures for intermediate results. Augmented enumeration operations can also include no-output operations such as changing file attributes or deleting a file, and cumulative operations such as counting total disk space usage. The parallelization is compatible with tree-level parallelization and storage-level parallelization. Disclosed technologies can be applied to other fields requiring scalable enumeration, such as database and network applications.

Grider, Gary A.↗

DOE OSTI2022

MEASUR - Manufacturing Energy Assessment Software for Utility Reduction

MEASUR your energy savings with the free DOE MEASUR software The Department of Energy (DOE), with Oak Ridge National Laboratory (ORNL), released version 1.0 of their energy efficiency software tool MEASUR (Manufacturing Energy Assessment Software for Utility Reduction). MEASUR has been available for several years as a beta version, being tested by industry experts and real users, and will continue to be updated and improved in the coming years. It is an integrated suite of tools to aid manufacturers in improving the efficiency of energy systems and equipment within a plant, including motors, pumps, fans, process heating, steam, and compressed air. Additionally, there are modules for wastewater energy analysis and to help perform energy treasure hunts. Several calculators are also included, allowing users to independently perform smaller calculations and analyses (such as estimating pump head, performing a fan traverse analysis, estimating waste heat recovery potential, and cataloging compressed air leaks). The MEASUR modules are based on previous DOE software tools that have been used by industry since the early 2000s (such as MotorMaster, AirMaster+, PSAT, PHAST, and FSAT). The original tools only ran on Windows operating systems, and by Windows 10, most of them were inoperable. DOE started their energy efficiency software tool revitalization effort in 2016, first with PSAT (for pumps), then began to integrate the other tools and expand their functionality and utility. The new MEASUR suite provides an extensively more user-friendly, modern, and versatile set of tools. All the assessment modules and most of the calculators have several visual components and graphs and detailed help text for every user input. To help reach international users, the tool utilizes Google translate and users can easily change unit systems, even converting existing user inputs if desired. The assessment files can be organized within the internal file system and easily shared to other users, regardless of their operating system. The entire suite is free, open-source, and can be downloaded on Windows, Mac, or Linux operating systems.

Accawi, Gina [Oak Ridge National Lab. (ORNL), Oak ↗

DOE OSTI2021

Battle of the Defaults: Extracting Performance Characteristics of HDF5 under Production Load

Popular parallel I/O libraries, such as HDF5, provide tuning parameters to obtain superior performance. However, the selection of effective parameters on production systems is complex due to the interdependence of I/O software and file system layers. Hence, application developers typically use the default parameters and often experience poor I/O performance. This work conducts a benchmarking-based analysis on the HDF5 behaviors with a wide variety of I/O patterns to extract performance characteristics under the production workload. To make the analysis well controlled, we exercise I/O benchmarks on POSIX-IO, MPI-IO, and HDF5 using the same I/O patterns and in the same jobs. To address high performance variability in production environments, we repeat the benchmarks across I/O patterns, storage devices, and time intervals. Based on the results, we identified consistent HDF5 behaviors that appropriate configurations and operations on dataset layout and file-metadata placement can improve performance significantly. We apply our findings and evaluate the tuned I/O library on two supercomputers: Summit and Cori. The results show that our tuned parameters can achieve more than 10× I/O performance speedup than that with default parameters on both systems, suggesting the effectiveness, stability, and generality of our solution.

Xie, Bing↗

DOE OSTI2020

Metadata compression

A computer-executable method, system, and computer program product for managing a Parallel-Logged File System (PLFS) on a data storage system, wherein the data storage system is in communication with an application that updates the data storage system with checkpoint data, the computer-executable method, system, and computer program product comprising receiving a first checkpoint including data from the application; analyzing the data in the first checkpoint to determine whether a pattern exists in the checkpoint data; and upon a positive determination, adding the pattern into PLFS.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

Design and Implementation of Papyrus: Parallel Aggregate Persistent Storage

A surprising development in recently announced HPC platforms is the addition of, sometimes massive amounts of, persistent (nonvolatile) memory (NVM) in order to increase memory capacity and compensate for plateauing I/O capabilities. However, there are no portable and scalable programming interfaces using aggregate NVM effectively. This paper introduces Papyrus: a new software system built to exploit emerging capability of NVM in HPC architectures. Papyrus (or Parallel Aggregate Persistent -YRU- Storage) is a novel programming system that provides features for scalable, aggregate, persistent memory in an extreme-scale system for typical HPC usage scenarios. Papyrus mainly consists of Papyrus Virtual File System (VFS) and Papyrus Template Container Library (TCL). Papyrus VFS provides a uniform aggregate NVM storage image across diverse NVM architectures. It enables Papyrus TCL to provide a portable and scalable high-level container programming interface whose data elements are distributed across multiple NVM nodes without requiring the user to handle complex communication, synchronization, replication, and consistency model. We evaluate Papyrus on two HPC systems, including UTK Beacon and NERSC Cori, using real NVM storage devices.

Kim, Jungwon↗

DOE OSTI2025

Accelerating Advanced Light Source Science Through Multi-Facility HPC Workflows

Synchrotron light sources support a wide array of techniques to investigate materials, often producing complex, high-volume data that challenge traditional workflows. At the Advanced Light Source (ALS), we developed infrastructure to move microtomography data over ESnet to ALCF and NERSC, where CPU- and GPU-based algorithms generate 3D reconstructed volumes of experimental samples. We employ two data movement and reconstruction models: real-time processing as data streams directly to NERSC compute nodes, and automated file transfer to NERSC and ALCF file systems. The streaming pipeline provides users with feedback in under ten seconds, while the file-based workflow produces high-quality reconstructions suitable for deeper analysis in 20-30 minutes. This infrastructure enables users to utilize HPC resources without direct access to backend systems. We plan to extend this architecture to more endstations, supporting our beamline scientists and users.

Abramov, David↗

DOE OSTI2017

SharP Hash: A High-Performing Distributed Hash for Extreme-Scale Systems

A high-performing distributed hash is critical for achieving performance in many applications and system software using extreme-scale systems. It is also a central part of many Big-Data frameworks including Memcached, file systems, and job schedulers. However, there is a lack of high-performing distributed hash implementations. In this work, we propose, design, and implement, SharP Hash, a high-performing, RDMA-based distributed hash for extreme-scale systems. SharP Hash's high performance is obtained through the use of high-performing networks and one-sided semantics. We perform an evaluation of SharP Hash and demonstrate its performance characteristics with a synthetic micro-benchmark and implementation of a Key Value (KV) store, Memcached.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2018

Analyzing the Impact of System Reliability Events on Applications in the Titan Supercomputer

Extreme-scale computing systems employ Reliability, Availability and Serviceability (RAS) mechanisms and infrastructure to log events from multiple system components. In this paper, we analyze RAS logs in conjunction with the application placement and scheduling database, in order to understand the impact of common RAS events on application performance. This study conducted on the records of about 2 million applications executed on Titan supercomputer provides important insights for system users, operators and computer science researchers. Specifically, we investigate the impact of RAS events on application performance and its variability by comparing cases where events are recorded with corresponding cases where no events are recorded. Such a statistical investigation is possible since we observed that system users tend to execute their applications multiple times. Our analysis reveals that most RAS events do impact application performance, although not always. We also find that different system components affect application performance differently. In particular, our investigation includes the following components: parallel file system processor, memory, graphics processing units, system and user software issues. Our work establishes the importance of providing feedback to system users for increasing operational efficiency of extreme-scale systems.

Ashraf, Rizwan↗

DOE OSTI2023

PoliMOR

PoliMOR is a scalable, automated, and customizable policy engine framework for multi-tiered parallel file systems. It is composed of single-purpose agents that handle tasks such as gathering file metadata, making policy decisions, and then executing actions based on those policies. These agents are designed to communicate using distributed message queues, allowing the number of individual agents to be scaled up as needed. PoliMOR automates the data management tasks by precluding the need for admin intervention. The agents in PoliMOR can be customized to integrate any utilities/tools that perform tasks like metadata scanning and data placement management.

Brumgard, Christopher↗

DOE OSTI2017

Space vehicle field unit and ground station system

A field unit and ground station may use commercial off-the-shelf (COTS) components and share a common architecture, where differences in functionality are governed by software. The field units and ground stations may be easy to deploy, relatively inexpensive, and be relatively easy to operate. A novel file system may be used where datagrams of a file may be stored across multiple drives and/or devices. The datagrams may be received out of order and reassembled at the receiving device.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2018

An Introduction to UNIX, Emacs, Latex, and Python

This document is designed to give a brief introduction to the UNIX Operating System, Emacs, Latex, and Python. Section 1 focuses on UNIX, and presents the basics of the file system, a variety of common commands, and a handful of slightly more in depth topics. Section 2 introduces Emacs and its somewhat unusual keyboard controls. In Section 3, the basics of creating a document in Latex are demonstrated. Finally, Section 4 provides the foundation needed to begin programming in Python.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2016

Space vehicle field unit and ground station system

Judd, Stephen↗

DOE OSTI2023

OCTOKV: An Agile Network-Based Key-Value Storage System with Robust Load Orchestration

In this paper, we propose OctoKV, an innovative network-based key-value storage system. OctoKV addresses the repetitive address translation overhead associated with traditional key-value stores running on file systems on the client side. To mitigate this overhead, we implemented the key-value store on the server side using NVMe-oF and a user-level NVMe driver. In particular, we employed fine-grained resource monitoring and load balancing based on heuristics to optimize I/O performance. OctoKV is deployed on a Linux cluster with Intel SPDK. The extensive evaluation shows that OctoKV achieves lower I/O response times in comparison to traditional approaches where key-value stores run on the client side. Also, the proposed load balancing strategies efficiently enhance I/O response times by equally distributing the workload from overloaded cores to other cores.

Khan, Awais↗

DOE OSTI2020

Method and system for reducing metadata overhead in a two-tier storage architecture

Example embodiments of the present invention relate to a method, a system, and a computer program product for maintaining dynamically loadable namespaces. The method includes presenting, to an application, a file system having a global single namespace (SN) comprising a plurality of dynamically-loadable namespaces (DLNs) maintained in a capacity tier (CT) of object storage of a storage system. In response to a job submitted by the application, dynamically loading a first dynamically-loadable namespace, including the metadata only for the first dynamically-loadable namespace, associated with the job from the capacity tier of object storage into a fast tier (FT) of storage of the storage system.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Evaluation of Best Practices in Mitigating Startup Costs on Leadership-Class Supercomputers

Supercomputers at Department of Energy (DOE) National Laboratories face a widening range of workloads, from traditional modeling and simulation to Artificial Intelligence model training or complex multi-stage workflows, and beyond. At DOE Leadership Computing Facilities like the Oak Ridge Leadership Computing Facility (OLCF), these workloads demand concurrent access to large portions of the supercomputer’s resources. Launching a job across massive supercomputers is challenging from the start; the file system struggles with a large backlog of metadata requests as tens of thousands of processes read thousands of the same files, and the compute job cannot start until this is completed. There are multiple existing approaches to calm this metadata storm, ranging from vendor-developed tools like sbcast to National Laboratory-developed tools like Spindle and Copper. In this paper, we benchmark and discuss three common approaches to improving compute job launch latencies on Frontier: Slurm’s sbcast tool, Spindle, and Copper. We evaluate these tools by measuring the launch latencies of four workloads: OSU Microbenchmark’s osu_init, Pynamic, Python import mpi4py, and Python import torch. We provide discussion of the results, highlighting data that meet expectations and that do not meet expectations.

Hagerty, Nick [ORNL] (ORCID:0000000330014414)↗

DOE OSTI2021

Exploiting user activeness for data retention in HPC systems

HPC systems typically rely on the fixed-lifetime (FLT) data retention strategy, which only considers temporal locality of data accesses to parallel file systems. However, our extensive analysis based on the leadership-class HPC system traces suggests that the FLT approach often fails to capture the dynamics in users' behavior and leads to undesired data purge. In this study, we propose an activeness-based data retention (ActiveDR) solution, which advocates considering the data retention approach from a holistic activeness-based perspective. By evaluating the frequency and impact of users' activities, ActiveDR prioritizes the file purge process for inactive users and rewards active users with extended file lifetime on parallel storage. Our extensive evaluations based on the traces of the prior Titan supercomputer show that, when reaching the same purge target, ActiveDR achieves up to 37% file miss reduction as compared to the current FLT retention methodology.

Zhang, Wei↗

DOE OSTI2022

The Evolution of Volatile Memory Forensics

The collection and analysis of volatile memory is a vibrant area of research in the cybersecurity community. The ever-evolving and growing threat landscape is trending towards fileless malware, which avoids traditional detection but can be found by examining a system’s random access memory (RAM). Additionally, volatile memory analysis offers great insight into other malicious vectors. It contains fragments of encrypted files’ contents, as well as lists of running processes, imported modules, and network connections, all of which are difficult or impossible to extract from the file system. For these compelling reasons, recent research efforts have focused on the collection of memory snapshots and methods to analyze them for the presence of malware. However, to the best of our knowledge, no current reviews or surveys exist that systematize the research on both memory acquisition and analysis. We fill that gap with this novel survey by exploring the state-of-the-art tools and techniques for volatile memory acquisition and analysis for malware identification. For memory acquisition methods, we explore the trade-offs many techniques make between snapshot quality, performance overhead, and security. For memory analysis, we examined the traditional forensic methods used, including signature-based methods, dynamic methods performed in a sandbox environment, as well as machine learning-based approaches. We summarize the currently available tools, and suggest areas for more research.

Nyholm, Hannah↗