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共 332 条记录，以下是1-10 订阅

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Security Testbed for Preempting Attacks against supercomputing Infrastructure

Security Testbed for Preempting Attacks against Supercomputi...

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2024 Workshops of the International conference for High Performance Computing, Networking, Storage and Analysis, SC Workshops 2024

作者： Cao, Phuong Kalbarczyk, Zbigniew Iyer, Ravishankar K. University of Illinois at Urbana-Champaign United States National Center for Supercomputing Applications United States

ISBN: (纸本)9798350355543

Preempting attacks targeting supercomputing systems before damage remains the top security priority. The main challenge is that noisy attack attempts and unreliable alerts often mask real attacks, causing permanent damages such as system integrity violations and data breaches. This paper describes a security testbed embedded in live traffic of a supercomputer at the National Center for supercomputing Applications (NCSA). The objective is to demonstrate attack preemption, i.e., stopping system compromise and data breaches at petascale supercomputers. Deployment of our testbed at NCSA enables the following key contributions:1)Insights from characterizing unique attack patterns found in real security logs of more than 200 security incidents curated in the past two decades at NCSA.2)Deployment of an attack visualization tool to illustrate the challenges of identifying real attacks in HPC environments and to support security operators in interactive attack analyses.3)Demonstrate the testbed's utility by running novel models, such as Factor Graph-Based models, to preempt a real-world ransomware *** results are broadly applicable to other supercomputing and high-performance computing centers. © 2024 ieee.

关键词： Factor Graphs Network Intrusion Preemption Probabilistic Graphical Models

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Achieving High-Performance Fault-Tolerant Routing in HyperX Interconnection Networks

Achieving High-Performance Fault-Tolerant Routing in HyperX ...

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2024 Workshops of the International conference for High Performance Computing, Networking, Storage and Analysis, SC Workshops 2024

作者： Camarero, Cristobal Cano, Alejandro Martinez, Carmen Beivide, Ramon Universidad de Cantabria Cantabria Spain Barcelona Supercomputing Center Spain

ISBN: (纸本)9798350355543

Interconnection networks are key actors that condition the performance of current large datacenter and supercomputer systems. Both topology and routing are critical aspects that must be carefully considered for a competitive system network design. Moreover, when daily failures are expected, this tandem should exhibit resilience and robustness. Low-diameter direct networks, including HyperX, are cheaper than typical Fat Trees. But, to be really competitive, they have to employ evolved routing algorithms to both balance traffic and tolerate *** this paper, SurePath, an efficient fault-tolerant routing mechanism for HyperX topologies is introduced and evaluated. SurePath leverages routes provided by standard routing algorithms and uses a deadlock avoidance mechanism based on an Up/Down escape subnetwork. This scheme not only prevents deadlock but also allows for a fault-tolerant solution for these networks. SurePath is thoroughly evaluated in the paper under different traffic patterns, showing no performance degradation under extremely faulty scenarios. © 2024 ieee.

关键词： adaptive routing deadlock avoidance fault-tolerance hyperx network

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Applying a Task-Based Approach to Distributed Machine Learning Workflows

Applying a Task-Based Approach to Distributed Machine Learni...

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2024 Workshops of the International conference for High Performance Computing, Networking, Storage and Analysis, SC Workshops 2024

作者： Vazquez-Novoa, Fernando Lezzi, Daniele Lordan, Francesc Baghdadi, Fatemeh Cirillo, Davide Barcelona Supercomputing Center Department of Computer Sciences Barcelona Spain Barcelona Supercomputing Center Department of Life Sciences Barcelona Spain

ISBN: (纸本)9798350355543

The growing demands across various scientific fields have led to a significant shift in applications that consume data at the edge of the computing continuum. These applications require unified programming models for the composition of components and coordinating the execution of computational workloads, including training machine learning (ML) models on distributed resources. Personalized healthcare often leverages data generated from wearable devices used to train ML models, can be benefited from distributed computing approaches. Specifically, stroke care can be greatly benefited from distributed ML with modifiable risk factors that can be monitored using wearable devices. In this work, we present an implementation that leverages distributed techniques for large-scale ML workflows using electrocardiogram (ECG) recordings for atrial fibrillation (AF) classification. The application was evaluated using the PhysioNet database, showcasing the potential of distributed, ML in stroke care, opening the way for future creation of more advanced models embedded in edge devices. © 2024 ieee.

关键词： ecg machine learning pycompss

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Improving the Discovery of Musical Heritage Documents in the Digital Libraries Federation Using Melodic Content Search and AI-based Optical Music Recognition 24

Improving the Discovery of Musical Heritage Documents in the...

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24th acm/ieee Joint conference on Digital Libraries-JCDL

作者： Pawlikowski, Konrad Nowak, Aleksandra Piniarska, Zuzanna Kalamoniak, Mateusz Parkola, Tomasz Lukasik, Ewa Chudy, Magdalena Poznan Supercomputing & Networking Ctr Poznan Poland Poznan Univ Tech Inst Comp Sci Poznan Poland Polish Acad Sci Inst Art Warsaw Poland

ISBN: (纸本)9798400710933

Digital Libraries Federation (FBC), the largest Polish aggregator in the cultural heritage domain, has recently been redesigned to enable full-text and melodic-content search functionalities aimed at improving the discovery and content-based retrieval of over 45k sheet music objects aggregated in FBC. Enabling music content retrieval required implementing three key changes to the FBC operations workflow: i) adapting its Solr search engine to process MEI documents;ii) adding AI-based Optical Music Recognition framework that converts the results to the MEI format to be processed by Solr;and iii) creating a brand new user interface for entering melodic queries and search results presentation.

关键词： digital libraries content aggregation melodic search OMR music information retrieval musical heritage

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Inspection of I/O Operations from System Call Traces using Directly-Follows-Graph

Inspection of I/O Operations from System Call Traces using D...

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2024 Workshops of the International conference for High Performance Computing, Networking, Storage and Analysis, SC Workshops 2024

作者： Sankaran, Aravind Zhukov, Ilya Frings, Wolfgang Bientinesi, Paolo Forschungszentrum Jülich Jülich Supercomputing Center Germany Umeå Universitet Department of Computer Science Sweden

ISBN: (纸本)9798350355543

We aim to identify the differences in Input/Output (I/O) behavior between multiple user programs through the inspection of system calls (i.e., requests made to the operating system). A typical program issues a large number of I/O requests to the operating system, thereby making the process of inspection challenging. In this paper, we address this challenge by presenting a methodology to synthesize I/O system call traces into a specific type of directed graph, known as the Directly-Follows-Graph (DFG). Based on the DFG, we present a technique to compare the traces from multiple programs or different configurations of the same program, such that it is possible to identify the differences in the I/O behavior. We apply our methodology to the IOR benchmark, and compare the contentions for file accesses when the benchmark is run with different options for file output and software interface. © 2024 ieee.

关键词： Directly-Follows Graph High-Performance Computing Input/Output Performance Analysis Process Mining strace

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Scalable In-Situ Visualization for Extreme-Scale SPH Simulations

Scalable In-Situ Visualization for Extreme-Scale SPH Simulat...

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2024 Workshops of the International conference for High Performance Computing, Networking, Storage and Analysis, SC Workshops 2024

作者： Zhu, Yiqing Simsek, Osman Seckin Favre, Jean M. Cabezon, Ruben Ciorba, Florina M. University of Basel Basel Switzerland Swiss National Supercomputing Centre Lugano Switzerland

ISBN: (纸本)9798350355543

Large-scale scientific simulations present significant challenges in data processing efficiency. This paper addresses the critical issue of I/O and data processing performance bottlenecks within the domain of extreme-scale Smoothed-particle Hydrodynamics (SPH) and gravity simulations. We present a novel I/O software architecture implemented in the scalable SPH-EXA framework [1], incorporating a variety of in-situ and post-hoc data analysis pipelines, facilitating rapid analysis and visualization of extreme-scale physical datasets. The performance of our I/O architecture is evaluated through comprehensive benchmarking across a wide range of data scales, conducted on the Piz Daint supercomputer [2]. © 2024 ieee.

关键词： extreme-scale HPC in-situ visualization SPH

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A Built-In Integrated Rowhammer, Rowpress, and Leakage Detection Sensor for DRAM 24

A Built-In Integrated Rowhammer, Rowpress, and Leakage Detec...

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43rd International conference on Computer-Aided Design, ICCAD 2024

作者： Rohbani, Nezam Pirayadi, Rouzbeh Soleimani, Mohammad Arman Kestelman, Adrian Cristal Unsal, Osman Sarbazi-Azad, Hamid Spain Department of Computer Engineering Sharif University of Technology Iran Barcelona Supercomputing Center Spain Department of Computer Engineering Sharif University of Technology Iran

ISBN: (纸本)9798400710773

The increasing density of DRAM chips has led to heightened susceptibility of memory cells to bit-flips. Rowhammer and Rowpress attacks on DRAMs have obtained significant attention due to their effectiveness in compromising system security and data integrity. A substantial portion of the previously proposed techniques for detecting rowhammer attacks focus on counting the number of row activations. However, these methods suffer from several limitations, including high overheads, lack of consideration for environmental conditions during DRAM operation, and limited tunability to detect rowpress attacks. To address these challenges, this work introduces a novel low-overhead built-in DRAM sensor designed specifically for detecting and locating rowhammer and rowpress attacks. The core idea behind the sensor is to utilize an additional non-operational DRAM sensor cell for each row. This auxiliary cell experiences the same potential rowhammer attacks as the other cells within that row. The sensor operates by controlling an extra precharged match-line based on the charge stored in the sensor cells. This sensor not only detects rowhammer attacks but also other environmental conditions that may impact DRAM cells retention time, such as temperature elevation or changes in operating voltage. Simulation results demonstrate that the proposed sensor detects all of the rowhammer attacks in the presence of process variation with a variance of up to 7.5% in circuit parameters. Furthermore, the area overhead introduced by the sensor remains about 1%, making it a promising solution for enhancing DRAM security with the minimum memory structure change. © 2024 Copyright is held by the owner/author(s).

关键词： Leak detection

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Understanding Data Movement in AMD Multi-GPU Systems with Infinity Fabric

Understanding Data Movement in AMD Multi-GPU Systems with In...

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2024 Workshops of the International conference for High Performance Computing, Networking, Storage and Analysis, SC Workshops 2024

作者： Schieffer, Gabin Shi, Ruimin Markidis, Stefano Herten, Andreas Faj, Jennifer Peng, Ivy KTH Royal Institute of Technology Stockholm Sweden Jülich Supercomputing Centre Jülich Germany

ISBN: (纸本)9798350355543

Modern GPU systems are constantly evolving to meet the needs of computing-intensive applications in scientific and machine learning domains. However, there is typically a gap between the hardware capacity and the achievable application performance. This work aims to provide a better understanding of the Infinity Fabric interconnects on AMD GPUs and CPUs. We propose a test and evaluation methodology for characterizing the performance of data movements on multi-GPU systems, stressing different communication options on AMD MI250X GPUs, including point-to-point and collective communication, and memory allocation strategies between GPUs, as well as the host CPU. In a single-node setup with four GPUs, we show that direct peer-to-peer memory accesses between GPUs and utilization of the RCCL library outperform MPI-based solutions in terms of memory/communication latency and bandwidth. Our test and evaluation method serves as a base for validating memory and communication strategies on a system and improving applications on AMD multi-GPU computing systems. © 2024 ieee.

关键词： AMD MI250X GPU AMD MI250X Memory System Performance Multi-GPU Programming

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Increasing Energy Efficiency of Astrophysics Simulations Through GPU Frequency Scaling

Increasing Energy Efficiency of Astrophysics Simulations Thr...

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2024 Workshops of the International conference for High Performance Computing, Networking, Storage and Analysis, SC Workshops 2024

作者： Simsek, Osman Seckin Piccinali, Jean-Guillaume Ciorba, Florina M. University of Basel Basel Switzerland Swiss National Supercomputing Centre Lugano Switzerland

ISBN: (纸本)9798350355543

The growing demand for high performance computing (HPC) necessitates significant energy consumption, posing a sustainability challenge for HPC centers, users, and society at large, especially in the face of stricter environmental regulations. While efforts exist to reduce overall system energy consumption, optimizations for GPU-based workloads, increasingly prevalent in HPC, has received insufficient attention for workload-specific energy efficiency optimizations. This work addresses this critical gap by proposing dynamic approaches to increase energy efficiency by instrumenting the simulation code with an open-source toolkit that enables accurate power and energy measurements for a wide range of CPU-GPU node architectures, as well as the instrumentation of the code controlling the GPU frequency dynamically. We further investigate the energy-performance trade-off by comparing both static and dynamic GPU frequency scaling strategies within SPH-EXA, a newly developed, open-source, and GPU-centric simulation framework specializing in astrophysical and cosmological simulations. Our findings demonstrate that code instrumentation enables detailed energy consumption acquisition beyond traditional HPC system monitoring, while dynamic frequency scaling of computational kernels achieves energy reduction with limited performance loss. This approach empowers researchers to develop more sustainable large-scale scientific simulations running mainly on GPUs. © 2024 ieee.

关键词： energy efficiency frequency scaling GPUs HPC large-scale simulations

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Analyzing HPC Utilization with PIKA and Vampir

Analyzing HPC Utilization with PIKA and Vampir

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2024 Workshops of the International conference for High Performance Computing, Networking, Storage and Analysis, SC Workshops 2024

作者： Williams, William R. Knespel, Maximilian Winkler, Frank Wesarg, Bert TUD Dresden University of Technology CIDS ZIH Dresden Germany GWT-TUD GmbH Dresden Germany

ISBN: (纸本)9798350355543

We present a set of tools to support analysis of the utilization of high performance computing (HPC) resources by extending PIKA, a site-level monitoring tool, and Vampir, a well-known performance analysis tool. We show an approach to transforming site-level data into a form that Vampir (and other application-level performance tools) can use to analyze cluster-level data as well. Finally, we show that the end product of this transformation allows useful performance analysis of cluster behavior. © 2024 ieee.

关键词： cluster monitoring performance analysis supercomputing

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