We present an approach for building performance models of multithreaded programs automatically. We use a combination of static and a dynamic analyses of a single representative run of the program to build its model. The model can predict performance of the program under a variety of configurations. This paper outlines how we construct the model and demonstrates how the resultant models accurately predict the performance %and resource utilization of complex multithreaded programs.
{"title":"Automated analysis of multithreaded programs for performance modeling","authors":"A. Tarvo, S. Reiss","doi":"10.1145/2591971.2592016","DOIUrl":"https://doi.org/10.1145/2591971.2592016","url":null,"abstract":"We present an approach for building performance models of multithreaded programs automatically. We use a combination of static and a dynamic analyses of a single representative run of the program to build its model. The model can predict performance of the program under a variety of configurations. This paper outlines how we construct the model and demonstrates how the resultant models accurately predict the performance %and resource utilization of complex multithreaded programs.","PeriodicalId":306456,"journal":{"name":"Measurement and Modeling of Computer Systems","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124994601","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}
Avner May, A. Chaintreau, Nitish Korula, Silvio Lattanzi
The impact of blogs and microblogging on the consumption of news is dramatic, as every day users rely more on these sources to decide what content to pay attention to. In this work, we empirically and theoretically analyze the dynamics of bloggers serving as intermediaries between the mass media and the general public. Our first contribution is to precisely describe the receiving and posting behaviors of today's social media users. For the first time, we study jointly the volume and popularity of URLs received and shared by users. We show that social media platforms exhibit a natural ``content curation'' process. Users and bloggers in particular obey two filtering laws: (1) a user who receives less content typically receives more popular content, and (2) a blogger who is less active typically posts disproportionately popular items. Our observations are remarkably consistent across 11 social media data sets. We find evidence of a variety of posting strategies, which motivates our second contribution: a theoretical understanding of the consequences of strategic posting on the stability of social media, and its ability to satisfy the interests of a diverse audience. We introduce a ``blog-positioning game'' and show that it can lead to ``efficient'' equilibria, in which users generally receive the content they are interested in. Interestingly, this model predicts that if users are overly ``picky'' when choosing who to follow, no pure strategy equilibria exists for the bloggers, and thus the game never converges. However, a bit of leniency by the readers in choosing which bloggers to follow is enough to guarantee convergence.
{"title":"Filter & follow: how social media foster content curation","authors":"Avner May, A. Chaintreau, Nitish Korula, Silvio Lattanzi","doi":"10.1145/2591971.2592010","DOIUrl":"https://doi.org/10.1145/2591971.2592010","url":null,"abstract":"The impact of blogs and microblogging on the consumption of news is dramatic, as every day users rely more on these sources to decide what content to pay attention to. In this work, we empirically and theoretically analyze the dynamics of bloggers serving as intermediaries between the mass media and the general public.\u0000 Our first contribution is to precisely describe the receiving and posting behaviors of today's social media users. For the first time, we study jointly the volume and popularity of URLs received and shared by users. We show that social media platforms exhibit a natural ``content curation'' process. Users and bloggers in particular obey two filtering laws: (1) a user who receives less content typically receives more popular content, and (2) a blogger who is less active typically posts disproportionately popular items. Our observations are remarkably consistent across 11 social media data sets. We find evidence of a variety of posting strategies, which motivates our second contribution: a theoretical understanding of the consequences of strategic posting on the stability of social media, and its ability to satisfy the interests of a diverse audience. We introduce a ``blog-positioning game'' and show that it can lead to ``efficient'' equilibria, in which users generally receive the content they are interested in. Interestingly, this model predicts that if users are overly ``picky'' when choosing who to follow, no pure strategy equilibria exists for the bloggers, and thus the game never converges. However, a bit of leniency by the readers in choosing which bloggers to follow is enough to guarantee convergence.","PeriodicalId":306456,"journal":{"name":"Measurement and Modeling of Computer Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130775355","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}
N. Nachiappan, Praveen Yedlapalli, N. Soundararajan, M. Kandemir, A. Sivasubramaniam, C. Das
As the demand for feature-rich mobile systems such as smartphones and tablets has outpaced other computing systems and is expected to continue at a faster rate, it is projected that SoCs with tens of cores and hundreds of IPs (or accelerator) will be designed to provide unprecedented level of features and functionality in future. Design of such mobile systems with required QoS and power budgets along with other design constraints will be a daunting task for computer architects since any ad hoc, piece-meal solution is unlikely to result in an optimal design. This requires early exploration of the complete design space to understand the system-level design trade-offs. To the best of our knowledge, there is no such publicly available tool to conduct a holistic evaluation of mobile platforms consisting of cores, IPs and system software. This paper presents GemDroid, a comprehensive simulation infrastructure to address these concerns. GemDroid has been designed by integrating the Android open-source emulator for facilitating execution of mobile applications, the GEM5 core simulator for analyzing the CPU and memory centric designs, and models for several IPs to collectively study their impact on system-level performance and power. Analyzing a spectrum of applications with GemDroid, we observed that the memory subsystem is a vital cog in the mobile platform because, it needs to handle both core and IP traffic, which have very different characteristics. Consequently, we present a heterogeneous memory controller (HMC) design, where we divide the memory physically into two address regions, where the first region with one memory controller (MC) handles core-specific application data and the second region with another MC handles all IP related data. The proposed modifications to the memory controller design results in an average 25% reduction in execution time for CPU bound applications, up to 11% reduction in frame drops, and on average 17% reduction in CPU busy time for on-screen (IP bound) applications.
{"title":"GemDroid: a framework to evaluate mobile platforms","authors":"N. Nachiappan, Praveen Yedlapalli, N. Soundararajan, M. Kandemir, A. Sivasubramaniam, C. Das","doi":"10.1145/2591971.2591973","DOIUrl":"https://doi.org/10.1145/2591971.2591973","url":null,"abstract":"As the demand for feature-rich mobile systems such as smartphones and tablets has outpaced other computing systems and is expected to continue at a faster rate, it is projected that SoCs with tens of cores and hundreds of IPs (or accelerator) will be designed to provide unprecedented level of features and functionality in future. Design of such mobile systems with required QoS and power budgets along with other design constraints will be a daunting task for computer architects since any ad hoc, piece-meal solution is unlikely to result in an optimal design. This requires early exploration of the complete design space to understand the system-level design trade-offs. To the best of our knowledge, there is no such publicly available tool to conduct a holistic evaluation of mobile platforms consisting of cores, IPs and system software.\u0000 This paper presents GemDroid, a comprehensive simulation infrastructure to address these concerns. GemDroid has been designed by integrating the Android open-source emulator for facilitating execution of mobile applications, the GEM5 core simulator for analyzing the CPU and memory centric designs, and models for several IPs to collectively study their impact on system-level performance and power. Analyzing a spectrum of applications with GemDroid, we observed that the memory subsystem is a vital cog in the mobile platform because, it needs to handle both core and IP traffic, which have very different characteristics. Consequently, we present a heterogeneous memory controller (HMC) design, where we divide the memory physically into two address regions, where the first region with one memory controller (MC) handles core-specific application data and the second region with another MC handles all IP related data. The proposed modifications to the memory controller design results in an average 25% reduction in execution time for CPU bound applications, up to 11% reduction in frame drops, and on average 17% reduction in CPU busy time for on-screen (IP bound) applications.","PeriodicalId":306456,"journal":{"name":"Measurement and Modeling of Computer Systems","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121953940","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}
In this paper, we consider the problem of distributed load shedding optimization for disaster recovery in smart grids. We develop distributed second-order interior-point based load shedding algorithms that enjoy a fast quadratic convergence rate. Our main contributions are two-fold: (i) We propose a rooted spanning tree based reformulation that enables our distributed algorithm design; (ii) Based on the spanning tree reformulation, we design distributed computation schemes for our proposed second-order interior-point based load shedding. Collectively, these results serve as an important first step in load shedding and disaster recovery that uses second-order distributed techniques.
{"title":"Distributed optimal load shedding for disaster recovery in smart electric power grids: a second-order approach","authors":"Jia Liu, Cathy H. Xia, N. Shroff, H. Sherali","doi":"10.1145/2591971.2592036","DOIUrl":"https://doi.org/10.1145/2591971.2592036","url":null,"abstract":"In this paper, we consider the problem of distributed load shedding optimization for disaster recovery in smart grids. We develop distributed second-order interior-point based load shedding algorithms that enjoy a fast quadratic convergence rate. Our main contributions are two-fold: (i) We propose a rooted spanning tree based reformulation that enables our distributed algorithm design; (ii) Based on the spanning tree reformulation, we design distributed computation schemes for our proposed second-order interior-point based load shedding. Collectively, these results serve as an important first step in load shedding and disaster recovery that uses second-order distributed techniques.","PeriodicalId":306456,"journal":{"name":"Measurement and Modeling of Computer Systems","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127440964","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}
Content Delivery Networks (CDNs) differ from other caching systems in terms of both workload characteristics and performance metrics. However, there has been little prior work on large-scale measurement and characterization of content requests and caching performance in CDNs. For workload characteristics, CDNs deal with extremely large content volume, high content diversity, and strong temporal dynamics. For performance metrics, other than hit ratio, CDNs also need to minimize the disk operations and the volume of traffic from origin servers. In this paper, we conduct a large-scale measurement study to characterize the content request patterns using real-world data from a commercial CDN provider.
{"title":"Revisiting caching in content delivery networks","authors":"M. Shafiq, A. Liu, Amir R. Khakpour","doi":"10.1145/2591971.2592021","DOIUrl":"https://doi.org/10.1145/2591971.2592021","url":null,"abstract":"Content Delivery Networks (CDNs) differ from other caching systems in terms of both workload characteristics and performance metrics. However, there has been little prior work on large-scale measurement and characterization of content requests and caching performance in CDNs. For workload characteristics, CDNs deal with extremely large content volume, high content diversity, and strong temporal dynamics. For performance metrics, other than hit ratio, CDNs also need to minimize the disk operations and the volume of traffic from origin servers. In this paper, we conduct a large-scale measurement study to characterize the content request patterns using real-world data from a commercial CDN provider.","PeriodicalId":306456,"journal":{"name":"Measurement and Modeling of Computer Systems","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122864974","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}
The increasing penetration of intermittent, unpredictable renewable energy sources such as wind energy, poses significant challenges for utility companies trying to incorporate renewable energy in their portfolio. In this work, we study the problem of conventional energy procurement in the presence of intermittent renewable resources. We model the problem as a variant of the newsvendor problem, in which the presence of renewable resources induces supply side uncertainty, and in which conventional energy may be procured in three stages to balance supply and demand. We compute closed-form expressions for the optimal energy procurement strategy and study the impact of increasing renewable penetration, and of proposed changes to the structure of electricity markets. We explicitly characterize the impact of a growing renewable penetration on the procurement policy by considering a scaling regime that models the aggregation of unpredictable renewable sources. A key insight from our results is that there is a separation between the impact of the stochastic nature of this aggregation, and the impact of market structure and forecast accuracy. Additionally, we study the impact on procurement of two proposed changes to the market structure: the addition and the placement of an intermediate market. We show that addition of an intermediate market does not necessarily increase the efficiency of utilization of renewable sources. Further, we show that the optimal placement of the intermediate market is insensitive to the level of renewable penetration.
{"title":"Energy procurement strategies in the presence of intermittent sources","authors":"J. Nair, S. Adlakha, A. Wierman","doi":"10.1145/2591971.2591982","DOIUrl":"https://doi.org/10.1145/2591971.2591982","url":null,"abstract":"The increasing penetration of intermittent, unpredictable renewable energy sources such as wind energy, poses significant challenges for utility companies trying to incorporate renewable energy in their portfolio. In this work, we study the problem of conventional energy procurement in the presence of intermittent renewable resources. We model the problem as a variant of the newsvendor problem, in which the presence of renewable resources induces supply side uncertainty, and in which conventional energy may be procured in three stages to balance supply and demand. We compute closed-form expressions for the optimal energy procurement strategy and study the impact of increasing renewable penetration, and of proposed changes to the structure of electricity markets. We explicitly characterize the impact of a growing renewable penetration on the procurement policy by considering a scaling regime that models the aggregation of unpredictable renewable sources. A key insight from our results is that there is a separation between the impact of the stochastic nature of this aggregation, and the impact of market structure and forecast accuracy. Additionally, we study the impact on procurement of two proposed changes to the market structure: the addition and the placement of an intermediate market. We show that addition of an intermediate market does not necessarily increase the efficiency of utilization of renewable sources. Further, we show that the optimal placement of the intermediate market is insensitive to the level of renewable penetration.","PeriodicalId":306456,"journal":{"name":"Measurement and Modeling of Computer Systems","volume":"38 10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125736455","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}
Shaoquan Zhang, Longbo Huang, Minghua Chen, Xin Liu
In online service systems, delay experienced by a user from the service request to the service completion is one of the most critical performance metrics. To improve user delay experience, in this paper, we investigate a novel aspect of system design: proactive serving, where the system can predict future user request arrivals and allocate its capacity to serve these upcoming requests proactively. In particular, we investigate the average user delay under proactive serving from a queuing theory perspective. We show that proactive serving reduces the average user delay exponentially (as a function of the prediction window size) under M/M/1 queueing models. Our simulation results show that, for G/G/1 queueing models, the average user delay also decreases significantly under proactive serving.
{"title":"Effect of proactive serving on user delay reduction in service systems","authors":"Shaoquan Zhang, Longbo Huang, Minghua Chen, Xin Liu","doi":"10.1145/2591971.2592024","DOIUrl":"https://doi.org/10.1145/2591971.2592024","url":null,"abstract":"In online service systems, delay experienced by a user from the service request to the service completion is one of the most critical performance metrics. To improve user delay experience, in this paper, we investigate a novel aspect of system design: proactive serving, where the system can predict future user request arrivals and allocate its capacity to serve these upcoming requests proactively. In particular, we investigate the average user delay under proactive serving from a queuing theory perspective. We show that proactive serving reduces the average user delay exponentially (as a function of the prediction window size) under M/M/1 queueing models. Our simulation results show that, for G/G/1 queueing models, the average user delay also decreases significantly under proactive serving.","PeriodicalId":306456,"journal":{"name":"Measurement and Modeling of Computer Systems","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121707708","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}
We develop shadow routing based online algorithms for the joint problem of application-to-VM and VM-to-PM assignments in a cloud environment. The asymptotic optimality of the shadow algorithm is proved and the performance is evaluated by simulations.
{"title":"Online algorithms for joint application-VM-physical-machine auto-scaling in a cloud","authors":"Yang Guo, A. Stolyar, A. Elwalid","doi":"10.1145/2591971.2592035","DOIUrl":"https://doi.org/10.1145/2591971.2592035","url":null,"abstract":"We develop shadow routing based online algorithms for the joint problem of application-to-VM and VM-to-PM assignments in a cloud environment. The asymptotic optimality of the shadow algorithm is proved and the performance is evaluated by simulations.","PeriodicalId":306456,"journal":{"name":"Measurement and Modeling of Computer Systems","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122289766","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}
Topic modeling refers to the task of inferring, only from data, the abstract ``topics" that occur in a collection of content. In this paper we look at latent topic modeling in a setting where unlike traditional topic modeling (a) there are no/few features (like words in documents) that are directly indicative of content topics (e.g. un-annotated videos and images, URLs etc.), but (b) users share and view content over a social network. We provide a new algorithm for inferring both the topics in which every user is interested, and thus also the topics in each content piece. We study its theoretical performance and demonstrate its empirical effectiveness over standard topic modeling algorithms.
{"title":"Topic modeling from network spread","authors":"Avik Ray, S. Sanghavi, S. Shakkottai","doi":"10.1145/2591971.2592018","DOIUrl":"https://doi.org/10.1145/2591971.2592018","url":null,"abstract":"Topic modeling refers to the task of inferring, only from data, the abstract ``topics\" that occur in a collection of content. In this paper we look at latent topic modeling in a setting where unlike traditional topic modeling (a) there are no/few features (like words in documents) that are directly indicative of content topics (e.g. un-annotated videos and images, URLs etc.), but (b) users share and view content over a social network. We provide a new algorithm for inferring both the topics in which every user is interested, and thus also the topics in each content piece. We study its theoretical performance and demonstrate its empirical effectiveness over standard topic modeling algorithms.","PeriodicalId":306456,"journal":{"name":"Measurement and Modeling of Computer Systems","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130249174","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}
S. Jyothi, Ankit Singla, Brighten Godfrey, A. Kolla
High throughput is a fundamental goal of network design. While myriad network topologies have been proposed to meet this goal, particularly in data center and HPC networking, a consistent and accurate method of evaluating a design's throughput performance and comparing it to past proposals is conspicuously absent. In this work, we develop a framework to benchmark the throughput of network topologies and apply this methodology to reveal insights about network structure. We show that despite being commonly used, cut-based metrics such as bisection bandwidth are the wrong metrics: they yield incorrect conclusions about the throughput performance of networks. We therefore measure flow-based throughput directly and show how to evaluate topologies with nearly-worst-case traffic matrices. We use the flow-based throughput metric to compare the throughput performance of a variety of computer networks. We have made our evaluation framework freely available to facilitate future work on design and evaluation of networks.
{"title":"Measuring throughput of data center network topologies","authors":"S. Jyothi, Ankit Singla, Brighten Godfrey, A. Kolla","doi":"10.1145/2591971.2592040","DOIUrl":"https://doi.org/10.1145/2591971.2592040","url":null,"abstract":"High throughput is a fundamental goal of network design. While myriad network topologies have been proposed to meet this goal, particularly in data center and HPC networking, a consistent and accurate method of evaluating a design's throughput performance and comparing it to past proposals is conspicuously absent. In this work, we develop a framework to benchmark the throughput of network topologies and apply this methodology to reveal insights about network structure. We show that despite being commonly used, cut-based metrics such as bisection bandwidth are the wrong metrics: they yield incorrect conclusions about the throughput performance of networks. We therefore measure flow-based throughput directly and show how to evaluate topologies with nearly-worst-case traffic matrices. We use the flow-based throughput metric to compare the throughput performance of a variety of computer networks. We have made our evaluation framework freely available to facilitate future work on design and evaluation of networks.","PeriodicalId":306456,"journal":{"name":"Measurement and Modeling of Computer Systems","volume":"6 11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130489938","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}
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