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IEEE International Conference on Big Data (Big Data)

作者： Ghandeharizadeh, Shahram Huang, Haoyu Univ Southern Calif Los Angeles CA 90007 USA

ISBN: (纸本)9781538650356

Hoagie is a plug-n-play workload and database generator to evaluate novel system architectures, design decisions, protocols, and algorithms. It uses published specifications to create a database of data items and a workload that references these data items. Hoagie's modular design enables an experimentalist to use it either offline or online. In offline mode, Hoagie outputs a trace file that can be used to issue requests to a target system. In online mode, Hoagie is plugged into an existing benchmark that invokes it to generate requests one at a time to its target system. We have made Hoagie open source to foster its future development.

关键词： workload generator benchmark performance

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A workload generator for Evaluating SMT Real-Time Systems 16

A Workload Generator for Evaluating SMT Real-Time Systems

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International Conference on High Performance Computing & Simulation (HPCS)

作者： Furio, Clara Feliu, Josue Petit, Salvador Duro, Jose Sahuquillo, Julio Univ Politecn Valencia Dept Informat Sistemas & Comp DISCA Valencia Spain

ISBN: (纸本)9781538678794

Real-time tasks have experience a significant complexity increase in the last years. We can find examples of real-time tasks in nowadays systems that control self-driving cars or multimedia systems, among others. To cope with the high performance requirements of such systems, real-time systems are moving from simple in-order processor to complex out-of-order multicore processors. Furthermore, we expect real-time systems to use simultaneous multithreading (SMT) processors in a near future since these architectures address two key design concerns of embedded systems, that is, they provide higher performance and power efficiency than single-threaded multicores. The main drawback that multicores and SMT architectures present from a real-time perspective is that they implement shared resources. Single-threaded multicores usually share the main memory and the LLC, and SMT processor share additionally most of the microarchitectural core resources. Processes running concurrently can interfere in the shared resources, which increases the performance variability and predictability of these systems. We expect an increasing effort in the next years to mitigate these drawbacks and implement real-time systems with multicore SMT processors. workload generation is a tedious and time-consuming task in the real-time research field because the workloads dispose of many parameters that should be correctly adjusted to provide flexible and representative workloads. Typically used workload generators, however, fail when designing workloads for theses architectures because they are not aware of the architectural characteristics of SMT systems. In this paper we present the task class-based (TCB) workload generator aimed at providing workloads to evaluate real-time systems with SMT multicore processors in an ease and automatized way.

关键词： Real-time systems Simultaneous multithreading (SMT) workload generator

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E2C: A Visual Simulator to Reinforce Education of Heterogeneous Computing Systems

E2C: A Visual Simulator to Reinforce Education of Heterogene...

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37th IEEE International Parallel and Distributed Processing Symposium (IPDPS)

作者： Mokhtari, Ali Rawls, Drake Huynh, Tony Green, Jeremiah Salehi, Mohsen Amini Univ Louisiana Lafayette Sch Comp & Informat High Performance Cloud Comp HPCC Lab Lafayette LA 70503 USA

ISBN: (纸本)9798350311990

Heterogeneity has been an indispensable aspect of distributed computing throughout the history of these systems. In particular, with the increasing popularity of accelerator technologies (e.g., GPUs and TPUs) and the emergence of domain-specific computing via ASICs and FPGA, the matter of heterogeneity and understanding its ramifications on the system performance has become more critical than ever before. However, it is challenging to effectively educate students about the potential impacts of heterogeneity on: (a) the performance of distributed systems;and (b) the logic of resource allocation methods to efficiently utilize the resources. Making use of the real infrastructure (such as those offered by the public cloud providers) for benchmarking the performance of heterogeneous machines, for different applications, with respect to different objectives, and under various workload intensities is cost- and time-prohibitive. Moreover, not all students (globally and nationally) have access or can afford such real infrastructure. To reinforce the quality of learning about various dimensions of heterogeneity, and to decrease the widening gap in education, we develop an open-source simulation tool, called E2C, that can help students researchers and practitioners to study any type of heterogeneous (or homogeneous) computing system and measure its performance under various system configurations. To make the learning curve shallow, E2C is equipped with an intuitive graphical user interface (GUI) that enables its users to easily examine system-level solutions (scheduling, load balancing, scalability, etc.) in a controlled environment within a short time and at no cost. In particular, E2C is a discrete event simulator that offers the following features: (i) simulating a heterogeneous computing system;(ii) implementing a newly developed scheduling method and plugging it into the system, (iii) measuring energy consumption and other output-related metrics;and (iv) powerful visual a

关键词： Cloud Computing Heterogeneous Computing Systems Learning Tool Simulator workload generator

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Automatic Evaluation and Comparison of Pub/Sub Systems Performance Improvements

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JOURNAL OF WEB ENGINEERING 2022年第4期21卷 1055-1079页

作者： Ramperez, Victor Soriano, Javier Lizcano, David Miguel, Carlos Univ Politecn Madrid UPM Madrid Spain Madrid Open Univ UDIMA Madrid Spain

Event-driven architectures are becoming more prevalent recently in multiple technological paradigms, especially in web applications, with message brokers being the cornerstone of these architectures. One of the most relevant implementations of these message brokers are content-based publish/subscribe systems. The performance of these systems is a critical factor for web engineering, since the web applications they support need to be reactive despite increases and fluctuations in workloads. However, an obstacle to the research of these systems is the lack of real and publicly available workloads, due to the privacy issue involved in disclosing the interests (subscriptions) of users and other commercial interests of the companies. In this paper we present a parameterizable automated system designed to syntactically translate workloads from different content-based publish/subscribe systems as a means to increase the availability of public workloads to solve the aforementioned problem. As a case study, we describe the evolution of a context-aware content-based publish/subscribe system (i.e. E-SilboPS) designed by the authors, which improves up to 5 times the performance of its previous version by reaching the maximum throughput limited by the physical resources of the hardware where it is deployed, as demonstrated by the conducted quantitative evaluation. Then, we validate the utility of the proposed automated workload generation system by using it to make the performance comparison between this new version E-SilboPS and one of the most cited publish/subscribe systems called PADRES, through a real trace of a massively multiplayer online game (MMOG) generated by the latter.

关键词： Content-based publish/subscribe workload generator elasticity

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Intelligent Block Level I/O workload Characterization for a Temporal and Spatial Locality Aware workload generator

Intelligent Block Level I/O Workload Characterization for a ...

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作者： Palanivel, Keerthi University of Minnesota

学位级别：M.S.E.E.

Performance of a system is a function of the system properties, and the workload seen by the system. One of the best ways to improve performance in systems is to tune or design the system based on the input workload. Localities in workloads greatly dictate the benefits one can extract from various cache hierarchies of the system stack. However, existing synthetic workload generators fail to reproduce traces that are a good representative of the original application, in terms of temporal and spatial localities. Additionally, existing workload generators are not flexible, and cannot handle cases that mimic changes in application behavior. Hence a probabilistic workload generator framework that produces synthetic trace with similar characteristics and locality as the original application, and has the support to accept or tune various workload parameter values to mimic existing or predicted workloads is presented. Apart from that, this workload generator has integration with a replay engine to issue trace IOs to a real system, or a storage simulator. Microsoft Research Traces were used for validating the tool, and the results show with up to 90% confidence that the ordering of synthetic trace is similar to the real trace. This tool can be used to study workloads in various environments like VM, cloud, database etc., and perform system optimizations or load studies.

关键词： Spatial Locality Stack Distance Temporal Locality workload Characterization workload generator

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Modeling Real-World Load Patterns for Benchmarking in Clouds and Clusters

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INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS 2020年第6期11卷 1-11页

作者： Qazi, Kashifuddin Manhattan Coll Dept Comp Sci Bronx NY 10471 USA

Cloud computing has currently permeated all walks of life. It has proven extremely useful for organizations and individual users to save costs by leasing compute resources that they need. This has led to an exponential growth in cloud computing based research and development. A substantial number of frameworks, approaches and techniques are being proposed to enhance various aspects of clouds, and add new features. One of the constant concerns in this scenario is creating a testbed that successfully reflects a real-world cloud datacenter. It is vital to simulate realistic, repeatable, standardized CPU and memory workloads to compare and evaluate the impact of the different approaches in a cloud environment. This paper introduces Cloudy, which is an open-source workload generator that can be used within cloud instances, Virtual Machines (VM), containers, or local hosts. Cloudy utilizes resource usage traces of machines from Google and Alibaba clusters to simulate up to 16000 different, real-world CPU and memory load patterns. The tool also provides a variety of machine metrics for each run, that can be used to evaluate and compare the performance of the VM, container or host. Additionally, it includes a web-based visualization component that offers a number of realtime statistics, as well as overall statistics of the workload such as seasonal trends, and autocorrelation. These statistics can be used to further analyze the real-world traces, and enhance the understanding of workloads in the cloud.

关键词： Cloud computing workload generator cluster computing

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Realistic and Scalable Benchmarking Cloud File Systems: Practices and Lessons from AliCloud

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IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS 2017年第11期28卷 3272-3285页

作者： Ren, Zujie Shi, Weisong Wan, Jian Cao, Feng Lin, Jiangbin Hangzhou Dianzi Univ Sch Comp Sci & Technol Hangzhou 310018 Zhejiang Peoples R China Wayne State Univ Dept Comp Sci Detroit MI 48202 USA Zhejiang Univ Sci & Technol Dept Software Engn Hangzhou 310023 Zhejiang Peoples R China AliCloud Comp Co Ltd Hangzhou 311121 Zhejiang Peoples R China

The past decade has witnessed the rapid boom of cloud computing. Many public cloud infrastructures have been implemented and serve millions of tenants. Cloud file systems, which take charge of petabyte-scale data storage, play a crucial role in the performance of cloud infrastructures. Typical cloud file systems, including GFS, HDFS and Ceph, have attracted notable research efforts for performance evaluation and optimization. However, due to the heterogeneity and complexity of I/O workload characteristics in cloud environments, it is still challenging to conduct an accurate and efficient performance evaluation. To address this problem, we collected a two-week I/O workload trace from a 2,500-node production cluster in AliCloud, which is one of the largest cloud providers in Asia. Using the AliCloud trace, we characterized the I/O workload and data distribution, and compared two cloud services in multiple perspectives, including the request arrival pattern, request size, data population and so on. A list of observations and implications were derived and applied to help design a cloud file system benchmarking suite, called Porcupine. Porcupine aims to deploy a scalable and efficient performance evaluation on cloud file systems using realistic I/O workloads. We conducted a group of validation experiments, which demonstrated that Porcupine can achieve high accuracy and scalability. This paper provides our experiences and lessons in generating I/O workloads and deploying performance tests on cloud file systems, which we believe will be insightful to the cloud computing community in general.

关键词： Cloud file systems workload generator performance benchmarking

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iGen: A Realistic Request generator for Cloud File Systems Benchmarking 9

iGen: A Realistic Request Generator for Cloud File Systems B...

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9th IEEE International Conference on Cloud Computing (CLOUD)

作者： Ren, Zujie Xu, Biao Shi, Weisong Ren, Yongjian Cao, Feng Lin, Jiangbin Ye, Zheng Hangzhou Dianzi Univ Sch Comp Sci Hangzhou Zhejiang Peoples R China Wayne State Univ Dept Comp Sci Detroit MI 48202 USA Alibaba Cloud Comp Ltd Pangu Team Beijing Peoples R China

ISBN: (纸本)9781509026197

Benchmarking is a traditional approach for system performance evaluation and optimization. Over the past decades, a variety of file systems, e.g., GFS, HDFS and Ceph, have been designed and implemented, serving as the key components in cloud infrastructures. With the mature of those cloud file systems, the demands for performance evaluation and comparison are also rising. However, due to the complexity and heterogeneity of I/O workloads in cloud infrastructures, it is still challenging to generate realistic I/O workloads. System developers often use traditional file system benchmarks and make inaccurate assumptions on workload generation, yielding to misleading results. To address this problem, we investigate the characteristics of I/O requests in a production cloud infrastructure at Alibaba Cloud Computing, which is one of the biggest cloud providers in Asia. We proposed a flexible framework iGen to mimic I/O request arrivals. One of the salient features of the iGen is that the request arrival process is modeled by three statistics properties, request arrival rate, inter-arrival time distribution, and request periodicity. According to these properties, the iGen can determine the sequence of requests and the inter-arrival time between two subsequent requests. We use the iGen to emulate a real workload that collected from Alibaba cloud platform. Experimental results show that high accuracy and flexibility of the iGen.

关键词： cloud file systems benchmarking workload generator

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A multi-tenant hierarchical modeling for cloud computing workload

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INTELLIGENT AUTOMATION AND SOFT COMPUTING 2016年第4期22卷 579-586页

作者： An, Chunyan Zhou, Jiantao Liu, Shuai Geihs, Kurt Inner Mongolia Univ Coll Comp Sci Hohhot Peoples R China Univ Kassel EECS Dept Kassel Germany

Diverse realistic workloads are urgently needed by SaaS providers and researchers to study the cloud environment. workload model is an important way to specify and produce workloads. However, existing workload models are usually simplified. They cannot comprehensively describe the variations of the behaviors in user-level, application-level and service level in real environment. Moreover, existing workload models are aimed to only specific applications. They fail to support multi-users, multi-applications and multi-service-units in one workload model. To solve the problem, a hierarchical workload modeling approach is proposed in this paper. The approach constructs a cloud workload model on three layers: User, application, service-units. At each layer two key time-varying variations are captured;amount and composition. Then the workload model is the superposition of the three layers. The approach provides a unified model for different applications and various user behaviors. The experiments give the hierarchical workload models of three examples, which applications are Bag-of-Tasks, MapReduce and self-contained service-units. The experimental results show the flexibility of the novel workload modeling. Finally, architecture of a workload generator based on the model is given.

关键词： Cloud computing hierarchical workload model workload generator

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Framework for Analyzing Android I/O Stack Behavior: From Generating the workload to Analyzing the Trace

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FUTURE INTERNET 2013年第4期5卷 591-610页

作者： Jeong, Sooman Lee, Kisung Hwang, Jungwoo Lee, Seongjin Won, Youjip Hanyang Univ Dept Comp & Software Seoul 133791 South Korea Samsung Elect Suwon 443742 South Korea

The existing I/O workload generators and trace capturing tools are not adaptable to generating nor capturing the I/O requests of Android apps. The Android platform needs proper tools to capture and replay real world workload in the Android platform to verify the result of benchmark tools. This paper introduces Android Storage Performance Analysis Tool, AndroStep, which is specifically designed for characterizing and analyzing the behavior of the I/O subsystem in Android based devices. The AndroStep consists of Mobibench (workload generator), MOST (Mobile Storage Analyzer), and Mobigen (workload replayer). Mobibench is an Android app that generates a filesystem as well as SQLite database operations. Mobibench can also vary the number of concurrent threads to examining the filesystem scalability to support concurrency, e.g., metadata updates, journal file creation/deletion. MOST captures the trace and extracts key filesystem access characteristics such as access pattern with respect to file types, ratio between random vs. sequential access, ratio between buffered vs. synchronous I/O, fraction of metadata accesses, etc. MOST implements reverse mapping feature (finding an inode for a given block) and retrospective reverse mapping (finding an inode for a deleted file). Mobigen is a trace capturing and replaying tool that is specifically designed to perform the user experiment without actual human intervention. Mobigen records the system calls generated from the user behavior and sanitizes the trace for replayable form. Mobigen can replay this trace on different Android platforms or with different I/O stack configurations. As an example of using AndroStep, we analyzed the performances of twelve Android smartphones and the SQLite performances on five different filesystems. AndroStep makes otherwise time consuming I/O stack analysis extremely versatile. AndroStep makes a significant contribution in terms of shedding light on internal behavior of the Android I/O stack.

关键词： Android workload generator analyzer replayer

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