2016 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS)最新文献

Message from the general chair 主席的口信

2016 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS) Pub Date : 2022-12-01 DOI: 10.1109/ISPASS.2016.7482065

Erik Hagersten

引用次数: 0

NoMali: Simulating a realistic graphics driver stack using a stub GPU NoMali:使用存根GPU模拟一个真实的图形驱动程序堆栈

2016 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS) Pub Date : 2016-06-02 DOI: 10.1109/ISPASS.2016.7482100

R. D. Jong, Andreas Sandberg

{"title":"NoMali: Simulating a realistic graphics driver stack using a stub GPU","authors":"R. D. Jong, Andreas Sandberg","doi":"10.1109/ISPASS.2016.7482100","DOIUrl":"https://doi.org/10.1109/ISPASS.2016.7482100","url":null,"abstract":"Since the advent of the smartphone, all high-end mobile devices have required graphics acceleration in the form of a GPU. Today, even low-power devices such as smartwatches use GPUs for rendering and composition. However, the computer architecture community has largely ignored these developments when evaluating new architecture proposals. A common approach when evaluating CPU designs for the mobile space has been to use software rendering instead of a GPU model. However, due to the ubiquity of GPUs in mobile devices, they are used in both 3D applications and 2D applications. For example, when running a 2D application such as the web browser in Android with a software renderer instead of a GPU, the CPU ends up executing twice as many instructions. Both the CPU characteristics and the memory system characteristics differ significantly between the browser and the software renderer. The software renderer typically executes tight loops of vector instructions, while the browser predominantly consists of integer instructions and complex control flow with hard-to-predict branches. Including software rendering results in unrepresentative benchmark performance. In this paper, we use gem5 to quantify the effects of software rendering on a set of common mobile workloads. We also introduce the NoMali stub GPU model that can be used as a drop-in replacement for a real Mali GPU model. This model behaves like a normal GPU, but does not render anything. Using this stub GPU, we demonstrate how most of the problems associated with software rendering can be avoided, while at the same time simulating a representative graphics stack.","PeriodicalId":416765,"journal":{"name":"2016 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130718383","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: 11

Characterizing Hadoop applications on microservers for performance and energy efficiency optimizations 在微服务器上描述Hadoop应用程序的性能和能效优化

2016 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS) Pub Date : 2016-04-17 DOI: 10.1109/ISPASS.2016.7482087

Maria Malik, Avesta Sasan, R. Joshi, Setareh Rafatirah, H. Homayoun

{"title":"Characterizing Hadoop applications on microservers for performance and energy efficiency optimizations","authors":"Maria Malik, Avesta Sasan, R. Joshi, Setareh Rafatirah, H. Homayoun","doi":"10.1109/ISPASS.2016.7482087","DOIUrl":"https://doi.org/10.1109/ISPASS.2016.7482087","url":null,"abstract":"The traditional low-power embedded processors such as Atom and ARM are entering the high-performance server market. At the same time, as the size of data grows, emerging Big Data applications require more and more server computational power that yields challenges to process data energy-efficiently using current high performance server architectures. Furthermore, physical design constraints, such as power and density have become the dominant limiting factor for scaling out servers. Numerous big data applications rely on using the Hadoop MapReduce framework to perform their analysis on large-scale datasets. Since Hadoop configuration parameters as well as architecture parameters directly affect the MapReduce job performance and energy-efficiency, system and architecture level parameters tuning is vital to maximize the energy efficiency. In this work, through methodical investigation of performance and power measurements, we demonstrate how the interplay among various Hadoop configurations and system and architecture level parameters affect the performance and energy-efficiency across various Hadoop applications.","PeriodicalId":416765,"journal":{"name":"2016 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116926827","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: 16

CoolSim: Eliminating traditional cache warming with fast, virtualized profiling CoolSim:通过快速、虚拟化的分析消除传统的缓存升温

2016 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS) Pub Date : 2016-04-17 DOI: 10.1109/ISPASS.2016.7482085

Nikos Nikoleris, Andreas Sandberg, Erik Hagersten, Trevor E. Carlson

引用次数: 2

MofySim: A mobile full-system simulation framework for energy consumption and performance analysis MofySim:用于能源消耗和性能分析的移动全系统仿真框架

2016 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS) Pub Date : 2016-04-17 DOI: 10.1109/ISPASS.2016.7482099

Minho Ju, Hyeonggyu Kim, Soontae Kim

{"title":"MofySim: A mobile full-system simulation framework for energy consumption and performance analysis","authors":"Minho Ju, Hyeonggyu Kim, Soontae Kim","doi":"10.1109/ISPASS.2016.7482099","DOIUrl":"https://doi.org/10.1109/ISPASS.2016.7482099","url":null,"abstract":"The analysis of energy consumption and performance is essential to design and optimize mobile systems because of their limited battery capacity. Full-system simulation provides detailed performance metrics for an entire system. Thus it has been widely used for designing and optimizing microarchitectures and mobile systems. The gem5 simulator provides full-system simulation based on the ARM architecture and Android for mobile systems. However, gem5 for mobile systems does not support wireless network interfaces and can not configure various networking environments such as network errors and network types. Furthermore, gem5 provides only performance statistics without power consumption data. This paper presents a mobile full-system simulation framework based on an enhanced gem5 that includes a simulated mobile system, a simulated server system, and a simulated Ethernet, which enables us to configure various networking environments, in addition to power models for the main components of mobile systems: CPU/caches, DRAM, network interfaces, and display. Using mobile applications and SPEC CPU2006 benchmarks, we show that the proposed mobile full-system simulator achieves performance accuracy within 26.8% error rate for various network packet loss rates, and power modeling accuracy within 12.8% error rate, compared with Nexus 5. This mobile full-system simulator considering the real networking environments provides the energy consumption and performance analysis of not only hardware components, but also application processes and threads at the same time. We also discovered energy-inefficient tasks and the inefficiency of the DVFS ondemand governor on network delays using the proposed mobile full-system simulation framework.","PeriodicalId":416765,"journal":{"name":"2016 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122483815","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: 16

JIT-assisted fast-forward embedding and instrumentation to enable fast, accurate, and agile simulation jit辅助的快进嵌入和仪器，以实现快速、准确和敏捷的仿真

2016 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS) Pub Date : 2016-04-17 DOI: 10.1109/ISPASS.2016.7482103

Berkin Ilbeyi, C. Batten

引用次数: 0

Elastic traces for fast and accurate system performance exploration 弹性轨迹，用于快速和准确的系统性能探索

2016 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS) Pub Date : 2016-04-17 DOI: 10.1109/ISPASS.2016.7482084

R. Jagtap, S. Diestelhorst, Andreas Hansson

引用次数: 1

MLC PCM main memory with accelerated read 具有加速读取功能的MLC PCM主存储器

2016 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS) Pub Date : 2016-04-17 DOI: 10.1109/ISPASS.2016.7482082

M. Arjomand, A. Jadidi, M. Kandemir, A. Sivasubramaniam, C. Das

引用次数: 9

Agave: A benchmark suite for exploring the complexities of the Android software stack Agave:一个用于探索Android软件栈复杂性的基准套件

2016 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS) Pub Date : 2016-04-17 DOI: 10.1109/ISPASS.2016.7482089

Martin K. Brown, Zachary Yannes, Michael Lustig, M. Sanati, S. Mckee, G. Tyson, S. Reinhardt

引用次数: 1

Workload characterization and optimization of TPC-H queries on Apache Spark Apache Spark上TPC-H查询的工作负载表征和优化

2016 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS) Pub Date : 2016-04-17 DOI: 10.1109/ISPASS.2016.7482079

Tatsuhiro Chiba, Tamiya Onodera

{"title":"Workload characterization and optimization of TPC-H queries on Apache Spark","authors":"Tatsuhiro Chiba, Tamiya Onodera","doi":"10.1109/ISPASS.2016.7482079","DOIUrl":"https://doi.org/10.1109/ISPASS.2016.7482079","url":null,"abstract":"Besides being an in-memory-oriented computing framework, Spark runs on top of Java Virtual Machines (JVMs), so JVM parameters must be tuned to improve Spark application performance. Misconfigured parameters and settings degrade performance. For example, using Java heaps that are too large often causes a long garbage collection pause time, which accounts for over 10-20% of application execution time. Moreover, recent computing nodes have many cores with simultaneous multi-threading technology and the processors on the node are connected via NUMA, so it is difficult to exploit best performance without taking into account of these hardware features. Thus, optimization in a full stack is also important. Not only JVM parameters but also OS parameters, Spark configuration, and application code based on CPU characteristics need to be optimized to take full advantage of underlying computing resources. In this paper, we used the TPC-H benchmark as our optimization case study and gathered many perspective logs such as application, JVM (e.g. GC and JIT), system utilization, and hardware events from a performance monitoring unit. We discuss current problems and introduce several JVM and OS parameter optimization approaches for accelerating Spark performance. As a result, our optimization exhibits 30-40% increase in speed on average and is up to 5x faster than the naive configuration.","PeriodicalId":416765,"journal":{"name":"2016 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS)","volume":"103 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116475796","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: 50