2021 International Symposium on Computer Architecture and High Performance Computing Workshops (SBAC-PADW)最新文献

Offloading the Training of an I/O Access Pattern Detector to the Cloud 将I/O访问模式检测器的训练卸载到云端

2021 International Symposium on Computer Architecture and High Performance Computing Workshops (SBAC-PADW) Pub Date : 2021-10-01 DOI: 10.1109/sbac-padw53941.2021.00013

C. Künas, M. Serpa, J. L. Bez, E. Padoin, P. Navaux

引用次数: 1

Quantifying and detecting HPC resource wastage in cloud environments 量化和检测云环境下的HPC资源浪费

2021 International Symposium on Computer Architecture and High Performance Computing Workshops (SBAC-PADW) Pub Date : 2021-10-01 DOI: 10.1109/sbac-padw53941.2021.00017

William F. C. Tavares, M. M. Assis, E. Borin

引用次数: 2

CLAP-Bot: a framework for automatic optimization of high-performance elastic applications on the Clouds CLAP-Bot:用于自动优化云上的高性能弹性应用程序的框架

2021 International Symposium on Computer Architecture and High Performance Computing Workshops (SBAC-PADW) Pub Date : 2021-10-01 DOI: 10.1109/sbac-padw53941.2021.00015

O. Napoli, Gustavo Ciotto Pinton, E. Borin

{"title":"CLAP-Bot: a framework for automatic optimization of high-performance elastic applications on the Clouds","authors":"O. Napoli, Gustavo Ciotto Pinton, E. Borin","doi":"10.1109/sbac-padw53941.2021.00015","DOIUrl":"https://doi.org/10.1109/sbac-padw53941.2021.00015","url":null,"abstract":"The computational cloud has become notorious due to its business model, where the user only pays to use the system, with no acquisition or maintenance costs. However, cloud providers such as AWS EC2 and Google Computing Engine offer several virtual machine types making it difficult to choose which of them is most suitable to the user’s application and objective.In this work, we present CLAP-Bot, a system that automatically monitors and adjusts the computing infrastructure based on some recipe. CLAP-Bot is built over CLAP, allowing creating and managing computational clusters in different cloud providers. The recipe is a component that can read application metrics and execute a set of actions on the infrastructure. The application monitor is decoupled from the recipe, allowing it to be used transparently with different applications. We show how CLAP-Bot works by implementing three dynamic provisioning policies as recipes and evaluating them. Besides that, together with CLAP-Bot we also present CLAP-Bot-Sim, a discrete event simulator that allows modeling the use of a given recipe without the need to instantiate any virtual machine. CLAP-Bot-Sim also allows modeling dynamic events, such as virtual machine interruptions and instance price oscillation over time. We show that CLAP-Bot-Sim can accurately simulate the effects of recipes on the computing infrastructure and can easily be interchanged with CLAP-Bot.","PeriodicalId":233108,"journal":{"name":"2021 International Symposium on Computer Architecture and High Performance Computing Workshops (SBAC-PADW)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126881927","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

WCC Program Committee WCC项目委员会

2021 International Symposium on Computer Architecture and High Performance Computing Workshops (SBAC-PADW) Pub Date : 2021-10-01 DOI: 10.1109/sbac-padw53941.2021.00009

引用次数: 0

Selecting efficient VM types to train deep learning models on Amazon SageMaker 选择高效的虚拟机类型在Amazon SageMaker上训练深度学习模型

2021 International Symposium on Computer Architecture and High Performance Computing Workshops (SBAC-PADW) Pub Date : 2021-10-01 DOI: 10.1109/SBAC-PADW53941.2021.00014

Rafael Keller Tesser, Alvaro Marques, E. Borin

{"title":"Selecting efficient VM types to train deep learning models on Amazon SageMaker","authors":"Rafael Keller Tesser, Alvaro Marques, E. Borin","doi":"10.1109/SBAC-PADW53941.2021.00014","DOIUrl":"https://doi.org/10.1109/SBAC-PADW53941.2021.00014","url":null,"abstract":"The cloud has become a popular environment for running Deep Learning (DL) applications. Public cloud providers charge by the amount time the resources are actually used, with the price by hour depending on the configuration of the chosen cloud instance. Instances are usually provided in the form of a VM that gives access to a certain hardware configuration, and may also come with a pre-configured software environment. More advanced, and theoretically faster, VMs are usually more expensive, but may not necessarily provide the best performance for all applications. Therefore, in order to choose the best instance (or VM type), users must consider the relative performances (and consequent cost) of different VMs when running their specific target application. Taking this into account, we propose a model to estimate the relative performance and cost of training deep learning applications running in different VM instances. This model is built upon observations derived from the performance profile of executions of three different DL applications, on 12 different public cloud instances. We argue that this model is a valuable tool for cloud users looking for optimal VM types to train their deep learning applications on the cloud.","PeriodicalId":233108,"journal":{"name":"2021 International Symposium on Computer Architecture and High Performance Computing Workshops (SBAC-PADW)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132682223","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Message from the WCC 2021 Workshop Chairs 来自2021年WCC工作坊主席的信息

2021 International Symposium on Computer Architecture and High Performance Computing Workshops (SBAC-PADW) Pub Date : 2021-10-01 DOI: 10.1109/sbac-padw53941.2021.00008

引用次数: 0

An evaluation of Cassandra NoSQL database on a low-power cluster Cassandra NoSQL数据库在低功耗集群上的性能评估

2021 International Symposium on Computer Architecture and High Performance Computing Workshops (SBAC-PADW) Pub Date : 2021-10-01 DOI: 10.1109/sbac-padw53941.2021.00012

Lucas B. da Silva, J. F. Lima

引用次数: 2

WAMCA 2021 Program Committee WAMCA 2021项目委员会

2021 International Symposium on Computer Architecture and High Performance Computing Workshops (SBAC-PADW) Pub Date : 2021-10-01 DOI: 10.1109/sbac-padw53941.2021.00007

引用次数: 0

A Memory Affinity Analysis of Scientific Applications on NUMA Platforms NUMA平台上科学应用的内存亲和性分析

2021 International Symposium on Computer Architecture and High Performance Computing Workshops (SBAC-PADW) Pub Date : 2021-10-01 DOI: 10.1109/sbac-padw53941.2021.00011

Rafael Gauna Trindade, J. F. Lima, A. Charão

引用次数: 0

A Cloud-Based Batch Processing System for Loosely-Coupled Applications 基于云的松耦合应用批处理系统

2021 International Symposium on Computer Architecture and High Performance Computing Workshops (SBAC-PADW) Pub Date : 2021-10-01 DOI: 10.1109/sbac-padw53941.2021.00018

Raoni Matos Smaneoto, T. Pereira, F. Brasileiro

{"title":"A Cloud-Based Batch Processing System for Loosely-Coupled Applications","authors":"Raoni Matos Smaneoto, T. Pereira, F. Brasileiro","doi":"10.1109/sbac-padw53941.2021.00018","DOIUrl":"https://doi.org/10.1109/sbac-padw53941.2021.00018","url":null,"abstract":"With the increased amount of data available for processing, and the increased need of processing this data, loosely-coupled batch applications have become very popular. Many batch applications require a high level of processing capacity, which leads us to the need of high performance computing infrastructures. This approach has been used for a long time, mainly for scientific purposes, and focused on the conventional environments for HPC, namely local clusters and supercomputers. The high-speed networks present in these systems are paramount for the execution of tightly-coupled scientific applications, but are wasted when executing loosely-coupled applications. Cloud infrastructures, on the other hand, provide a more appropriate infrastructure to support such loosely-coupled applications. Unfortunately, the user experience in cloud systems is completely different from that of conventional batch systems, mainly because the infrastructure needs to be deployed and subsequently released, to achieve the desired gains. In this paper we propose the architecture of a batch processing system that takes advantage of common features of cloud infrastructures to minimize cost and waiting time, while providing a user experience that is similar to conventional HPC systems.","PeriodicalId":233108,"journal":{"name":"2021 International Symposium on Computer Architecture and High Performance Computing Workshops (SBAC-PADW)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132849044","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0