Recently, mobile ad hoc networks (MANETs) have received a lot of attention and can be used effectively for fast resource sharing due to their flexibility, self-organization and simple implementation. However, resource discovery is an important and challenging issue in mobile ad hoc networks because of their dynamic nature, topology variations and limited resources. In this paper, we propose a middleware architecture based on the publish-subscribe system that can be used to discover and locate of resources in mobile ad hoc networks. This middleware provides capabilities to adjust Quality of Service, load balancing and prioritization and can work well under broker failures. The simulation results show that our approach significantly reduces message cost and discovery delay, while improving resource availability.
{"title":"Publish/Subscribe Middleware for Resource Discovery in MANET","authors":"Malihe Saghian, R. Ravanmehr","doi":"10.1109/CCGrid.2015.39","DOIUrl":"https://doi.org/10.1109/CCGrid.2015.39","url":null,"abstract":"Recently, mobile ad hoc networks (MANETs) have received a lot of attention and can be used effectively for fast resource sharing due to their flexibility, self-organization and simple implementation. However, resource discovery is an important and challenging issue in mobile ad hoc networks because of their dynamic nature, topology variations and limited resources. In this paper, we propose a middleware architecture based on the publish-subscribe system that can be used to discover and locate of resources in mobile ad hoc networks. This middleware provides capabilities to adjust Quality of Service, load balancing and prioritization and can work well under broker failures. The simulation results show that our approach significantly reduces message cost and discovery delay, while improving resource availability.","PeriodicalId":6664,"journal":{"name":"2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing","volume":"13 1","pages":"1205-1208"},"PeriodicalIF":0.0,"publicationDate":"2015-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91208824","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}
Erasure codes are widely used in modern distributed storage systems to prevent data loss and server failures. Regenerating codes are a class of erasure codes that trades storage efficiency and computation for repair bandwidth reduction. However, their non-unified coding parameters and huge computation overhead prohibit their applications. Hence, we first propose a family of Functional Regenerating Codes (FRCs) with uncoded repair, balancing storage efficiency and repair bandwidth with general parameters. FRCs take advantage of a heuristic repair algorithm, which makes efforts to employ as little repair bandwidth as possible. Second, we optimize encoding by constructing the generator matrix with a bitmatrix, so encoding of FRCs can be executed by fast bitwise XORs. Further, we also optimize repairing with the Scheduled Shift Multiplication (SSM) algorithm, which accelerates the matrix product over the Galois field during repair. Compared to the traditional table-lookup multiplication algorithm, our SSM algorithm gains 1.2~2X speed-up.
{"title":"General Functional Regenerating Codes with Uncoded Repair for Distributed Storage System","authors":"Qing Liu, D. Feng, Zhan Shi, Min Fu","doi":"10.1109/CCGrid.2015.38","DOIUrl":"https://doi.org/10.1109/CCGrid.2015.38","url":null,"abstract":"Erasure codes are widely used in modern distributed storage systems to prevent data loss and server failures. Regenerating codes are a class of erasure codes that trades storage efficiency and computation for repair bandwidth reduction. However, their non-unified coding parameters and huge computation overhead prohibit their applications. Hence, we first propose a family of Functional Regenerating Codes (FRCs) with uncoded repair, balancing storage efficiency and repair bandwidth with general parameters. FRCs take advantage of a heuristic repair algorithm, which makes efforts to employ as little repair bandwidth as possible. Second, we optimize encoding by constructing the generator matrix with a bitmatrix, so encoding of FRCs can be executed by fast bitwise XORs. Further, we also optimize repairing with the Scheduled Shift Multiplication (SSM) algorithm, which accelerates the matrix product over the Galois field during repair. Compared to the traditional table-lookup multiplication algorithm, our SSM algorithm gains 1.2~2X speed-up.","PeriodicalId":6664,"journal":{"name":"2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing","volume":"12 1","pages":"372-381"},"PeriodicalIF":0.0,"publicationDate":"2015-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77149934","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 the Network Function Virtualization (NFV) architecture, Network Service Chaining (NSC) is consisted in a certain order of network elements so that it can provide flexible network services to users. Due to the complexity of network infrastructure, creating a service chain requires high operation cost especially in carrier-grade network service providers and supporting stringent QoS requirements is also a challenge. Although several vendors provide various solutions for the NSC, there is only few information and the detailed algorithm or implementation logic is hidden. This paper presents an NSC algorithm in NFV that assures QoS from the perspective of service providers. In order to formulate NSC path selection problem, we apply the NP complete genetic algorithm. The evaluation results show that the proposed algorithm minimizes the operation cost of service providers by approximately 10.6% while the requested QoS targets is not violated.
在网络功能虚拟化(Network Function Virtualization, NFV)架构中，网络服务链(Network Service chains, NSC)是由网元按照一定的顺序组成，为用户提供灵活的网络服务。由于网络基础设施的复杂性，创建服务链需要很高的运营成本，特别是在运营商级网络服务提供商中，并且支持严格的QoS要求也是一个挑战。虽然有几个供应商提供了各种NSC解决方案，但信息很少，并且隐藏了详细的算法或实现逻辑。从服务提供商的角度出发，提出了一种NFV中的NSC算法来保证服务质量。为了求解NSC路径选择问题，我们采用了NP完全遗传算法。评估结果表明，该算法在不违背QoS目标的前提下，将服务提供商的运营成本降低了约10.6%。
{"title":"A QoS Assured Network Service Chaining Algorithm in Network Function Virtualization Architecture","authors":"Taekhee Kim, S. Kim, Kwonyong Lee, Sungyong Park","doi":"10.1109/CCGrid.2015.135","DOIUrl":"https://doi.org/10.1109/CCGrid.2015.135","url":null,"abstract":"In the Network Function Virtualization (NFV) architecture, Network Service Chaining (NSC) is consisted in a certain order of network elements so that it can provide flexible network services to users. Due to the complexity of network infrastructure, creating a service chain requires high operation cost especially in carrier-grade network service providers and supporting stringent QoS requirements is also a challenge. Although several vendors provide various solutions for the NSC, there is only few information and the detailed algorithm or implementation logic is hidden. This paper presents an NSC algorithm in NFV that assures QoS from the perspective of service providers. In order to formulate NSC path selection problem, we apply the NP complete genetic algorithm. The evaluation results show that the proposed algorithm minimizes the operation cost of service providers by approximately 10.6% while the requested QoS targets is not violated.","PeriodicalId":6664,"journal":{"name":"2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing","volume":"110 1","pages":"1221-1224"},"PeriodicalIF":0.0,"publicationDate":"2015-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79245376","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 cloud computing, an important issue is virtual machine placement (VMP), selecting the most suitable set of physical hosts for a set of virtual machines. In this paper, we present a novel solution to the VMP problem called VMPMBBO. Our scheme treats the VMP problem as a complex system, and utilizes the biogeography-based optimization (BBO) technique to optimize the virtual machine placement that minimizes power consumption, resource waste, server unevenness, inter-VM traffic, storage traffic and migration time at the same time. Compared with three existing multi-objective VMP optimization algorithms, VMPMBBO has better convergence characteristics and is more computationally efficient. VMPMBBO is also robust. Extensive experiments are conducted using synthetic data from related literatures. The results confirm the effectiveness, efficiency, and robustness of the proposed approach. To the best of our knowledge, this work is the first approach that applies BBO and complex system optimization to virtual machine placement (VMP).
{"title":"A Multi-objective Biogeography-Based Optimization for Virtual Machine Placement","authors":"Q. Zheng, R. Li, Xiuqi Li, Jie Wu","doi":"10.1109/CCGrid.2015.25","DOIUrl":"https://doi.org/10.1109/CCGrid.2015.25","url":null,"abstract":"In cloud computing, an important issue is virtual machine placement (VMP), selecting the most suitable set of physical hosts for a set of virtual machines. In this paper, we present a novel solution to the VMP problem called VMPMBBO. Our scheme treats the VMP problem as a complex system, and utilizes the biogeography-based optimization (BBO) technique to optimize the virtual machine placement that minimizes power consumption, resource waste, server unevenness, inter-VM traffic, storage traffic and migration time at the same time. Compared with three existing multi-objective VMP optimization algorithms, VMPMBBO has better convergence characteristics and is more computationally efficient. VMPMBBO is also robust. Extensive experiments are conducted using synthetic data from related literatures. The results confirm the effectiveness, efficiency, and robustness of the proposed approach. To the best of our knowledge, this work is the first approach that applies BBO and complex system optimization to virtual machine placement (VMP).","PeriodicalId":6664,"journal":{"name":"2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing","volume":"9 1","pages":"687-696"},"PeriodicalIF":0.0,"publicationDate":"2015-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79638132","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}
These years energy consumption has become the main constraint for the further improvement of computing ability of data centers. In this work, the energy efficient resource management strategies for web servers (one typical class of data centers) are discussed. We firstly introduce the daily pattern of requests sent to web servers which indicates that a simple off-line resource provisioning method would-be effective for web servers. Then, the energy efficiency of two load distribution algorithms are compared by replaying subset of a real-world Wikipedia trace in our local web service environment. The results show that, compared with the relative load distribution (RLB) algorithm, the adaptive load distribution (ALD) algorithm proposed in our previous work is more energy efficient. Finally, we demonstrate a potential that much energy can be saved by shutting down the idle nodes.
{"title":"Improving Energy Efficiency of Web Servers by Using a Load Distribution Algorithm and Shutting Down Idle Nodes","authors":"Kai Chen, Jörg Lenhardt, W. Schiffmann","doi":"10.1109/CCGrid.2015.75","DOIUrl":"https://doi.org/10.1109/CCGrid.2015.75","url":null,"abstract":"These years energy consumption has become the main constraint for the further improvement of computing ability of data centers. In this work, the energy efficient resource management strategies for web servers (one typical class of data centers) are discussed. We firstly introduce the daily pattern of requests sent to web servers which indicates that a simple off-line resource provisioning method would-be effective for web servers. Then, the energy efficiency of two load distribution algorithms are compared by replaying subset of a real-world Wikipedia trace in our local web service environment. The results show that, compared with the relative load distribution (RLB) algorithm, the adaptive load distribution (ALD) algorithm proposed in our previous work is more energy efficient. Finally, we demonstrate a potential that much energy can be saved by shutting down the idle nodes.","PeriodicalId":6664,"journal":{"name":"2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing","volume":"19 1","pages":"745-748"},"PeriodicalIF":0.0,"publicationDate":"2015-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82896309","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}
Anshuman Biswas, S. Majumdar, B. Nandy, A. El-Haraki
This paper presents a novel technique for auto-scaling cloud resources provided by an intermediary enterprise which services requests from a client enterprise. The intermediary enterprise acquires resources on demand from a public cloud. A broker is deployed by the intermediary enterprise to handle client requests with service level agreements (SLAs). A reactive auto-scaling algorithm is activated on request arrival and achieves auto-scaling by acquiring new resources for serving the recently arrived request. The technique ensures that a grade of service specified by the client enterprise is satisfied and is based on a profit analysis for the intermediary enterprise. A resources is released after the last request allocated on the resource has completed execution. The paper demonstrates that the proposed reactive auto-scaling technique can effectively lead to a profit for the intermediary enterprise as well as a reduction of cost for the client enterprise.
{"title":"An Auto-Scaling Framework for Controlling Enterprise Resources on Clouds","authors":"Anshuman Biswas, S. Majumdar, B. Nandy, A. El-Haraki","doi":"10.1109/CCGrid.2015.120","DOIUrl":"https://doi.org/10.1109/CCGrid.2015.120","url":null,"abstract":"This paper presents a novel technique for auto-scaling cloud resources provided by an intermediary enterprise which services requests from a client enterprise. The intermediary enterprise acquires resources on demand from a public cloud. A broker is deployed by the intermediary enterprise to handle client requests with service level agreements (SLAs). A reactive auto-scaling algorithm is activated on request arrival and achieves auto-scaling by acquiring new resources for serving the recently arrived request. The technique ensures that a grade of service specified by the client enterprise is satisfied and is based on a profit analysis for the intermediary enterprise. A resources is released after the last request allocated on the resource has completed execution. The paper demonstrates that the proposed reactive auto-scaling technique can effectively lead to a profit for the intermediary enterprise as well as a reduction of cost for the client enterprise.","PeriodicalId":6664,"journal":{"name":"2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing","volume":"35 1","pages":"971-980"},"PeriodicalIF":0.0,"publicationDate":"2015-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90397213","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}
Ying He, Jian Wang, Xue-xia Zhong, Lin Mei, Zhi-zong Wu
Most of the existing methods for generating a visual dictionary SIFT based on local characteristics, and adopt the common K-means clustering method to get the visual dictionary. But when the image vector dimension of the local feature is growing higher, the vector distribution of the local characteristics becomes sparse, resulting in the high correlation distance between the image vectors and reducing the comparability and universality of the visual patterns. According to the above problem, based on the local SIFT features, this paper introduced a Principal Component Analysis Hierarchical clustering method (PCAH) for generating the visual dictionary. This method can effectively ease the feature dimension disaster and obtain better stability. In addition, this method can solve the problem because of high dimension and structure complexity in the feature space of the images efficiently, and can get better performance in generating the visual dictionary. The experiment is executed on the pedestrians dataset Test_dataset1(our own dataset), pos, the scene classification dataset Upright vs Inverted, and the behavior classification dataset Stanford40_JPEGImages. And the datasets are divided into two groups based on the number of the SIFT features (one is less than 300 and the other is more than 5000). We adopt the Silhouette index and the computation time as the evaluation index. The experiment results indicate that comparing with the K-means clustering algorithm, the proposed PCA-based Hierarchical clustering method (PCAH) can reach higher quality visual words. At the same time, the computation speed of the PCAH clustering method is faster.
{"title":"PCAH: A PCA-Based Hierarchical Clustering Method for Visual Words Construction","authors":"Ying He, Jian Wang, Xue-xia Zhong, Lin Mei, Zhi-zong Wu","doi":"10.1109/CCGrid.2015.33","DOIUrl":"https://doi.org/10.1109/CCGrid.2015.33","url":null,"abstract":"Most of the existing methods for generating a visual dictionary SIFT based on local characteristics, and adopt the common K-means clustering method to get the visual dictionary. But when the image vector dimension of the local feature is growing higher, the vector distribution of the local characteristics becomes sparse, resulting in the high correlation distance between the image vectors and reducing the comparability and universality of the visual patterns. According to the above problem, based on the local SIFT features, this paper introduced a Principal Component Analysis Hierarchical clustering method (PCAH) for generating the visual dictionary. This method can effectively ease the feature dimension disaster and obtain better stability. In addition, this method can solve the problem because of high dimension and structure complexity in the feature space of the images efficiently, and can get better performance in generating the visual dictionary. The experiment is executed on the pedestrians dataset Test_dataset1(our own dataset), pos, the scene classification dataset Upright vs Inverted, and the behavior classification dataset Stanford40_JPEGImages. And the datasets are divided into two groups based on the number of the SIFT features (one is less than 300 and the other is more than 5000). We adopt the Silhouette index and the computation time as the evaluation index. The experiment results indicate that comparing with the K-means clustering algorithm, the proposed PCA-based Hierarchical clustering method (PCAH) can reach higher quality visual words. At the same time, the computation speed of the PCAH clustering method is faster.","PeriodicalId":6664,"journal":{"name":"2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing","volume":"102 1","pages":"1009-1018"},"PeriodicalIF":0.0,"publicationDate":"2015-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75766305","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}
Recent trends show that cloud computing is growing to span more and more globally distributed data centers. For geo-distributed data centers, there is an increasing need for scheduling algorithms to place tasks across data centers, by jointly considering data and computation. This scheduling must deal with situations such as wide-area distributed data, data sharing, WAN bandwidth costs and data center capacity limits, while also minimizing completion time. However, this kind of scheduling problems is known to be NP-Hard. In this paper, inspired by real applications in astronomy field, we propose a two-phase scheduling algorithm that addresses these challenges. The mapping phase groups tasks considering the data-sharing relations, and dispatches groups to data centers by way of one-to-one correspondence. The reassigning phase balances the completion time across data centers according to relations between tasks and groups. We utilize the real China-Astronomy-Cloud model and typical applications to evaluate our proposal. Simulations show that our algorithm obtains up to 22% better completion time and effectively reduces the amount of data transfers compared with other similar scheduling algorithms.
{"title":"Joint Scheduling of Data and Computation in Geo-Distributed Cloud Systems","authors":"Lingyan Yin, Ji-zhou Sun, Laiping Zhao, Chenzhou Cui, Jian Xiao, Ce Yu","doi":"10.1109/CCGrid.2015.83","DOIUrl":"https://doi.org/10.1109/CCGrid.2015.83","url":null,"abstract":"Recent trends show that cloud computing is growing to span more and more globally distributed data centers. For geo-distributed data centers, there is an increasing need for scheduling algorithms to place tasks across data centers, by jointly considering data and computation. This scheduling must deal with situations such as wide-area distributed data, data sharing, WAN bandwidth costs and data center capacity limits, while also minimizing completion time. However, this kind of scheduling problems is known to be NP-Hard. In this paper, inspired by real applications in astronomy field, we propose a two-phase scheduling algorithm that addresses these challenges. The mapping phase groups tasks considering the data-sharing relations, and dispatches groups to data centers by way of one-to-one correspondence. The reassigning phase balances the completion time across data centers according to relations between tasks and groups. We utilize the real China-Astronomy-Cloud model and typical applications to evaluate our proposal. Simulations show that our algorithm obtains up to 22% better completion time and effectively reduces the amount of data transfers compared with other similar scheduling algorithms.","PeriodicalId":6664,"journal":{"name":"2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing","volume":"67 1","pages":"657-666"},"PeriodicalIF":0.0,"publicationDate":"2015-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75833125","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}
Lantian Guo, Xianrong Zheng, Chen Ding, Dejun Mu, Zhe Li
Cloud computing is an attractive platform which offers on-demand resources as services. When many cloud services are available, some may have similar or same functionalities. So cloud service recommendation, which can help users to select the services based on their preferences, become an important technique for cloud services. In this paper, we review the relevant technologies that can perform cloud service recommendation. First, we introduce the web service selection and recommendation technologies. Next, we describe QoS measurement for cloud service and different recommendation methods focusing on Collaborative filtering. Third, we discuss the research challenges and opportunities for cloud service recommendation.
{"title":"Cloud Service Recommendation: State of the Art and Research Challenges","authors":"Lantian Guo, Xianrong Zheng, Chen Ding, Dejun Mu, Zhe Li","doi":"10.1109/CCGrid.2015.144","DOIUrl":"https://doi.org/10.1109/CCGrid.2015.144","url":null,"abstract":"Cloud computing is an attractive platform which offers on-demand resources as services. When many cloud services are available, some may have similar or same functionalities. So cloud service recommendation, which can help users to select the services based on their preferences, become an important technique for cloud services. In this paper, we review the relevant technologies that can perform cloud service recommendation. First, we introduce the web service selection and recommendation technologies. Next, we describe QoS measurement for cloud service and different recommendation methods focusing on Collaborative filtering. Third, we discuss the research challenges and opportunities for cloud service recommendation.","PeriodicalId":6664,"journal":{"name":"2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing","volume":"76 1","pages":"761-764"},"PeriodicalIF":0.0,"publicationDate":"2015-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74685931","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}
To migrate complex sequential code to multicore, profiling is often used on sequential executions to find opportunities for parallelization. In non-scientific code, the potential parallelism often resides in while-loops rather than for-loops. The do-all model used in the past by many studies cannot detect this type of parallelism. A new, task-based model has been used by a number of recent studies and shown safe for general loops and functions. This paper presents a feedback-based compiler that measures the amount of safe task parallelism in a program and ranks the potential candidates. It solves two problems unique for task analysis. The first is the relation between loop parallelism and function parallelism. The second is the effect of the calling context. The new tool is built in the GCC compiler and used to analyze the entire suite of SPEC 2006 integer benchmarks.
{"title":"Assessing Safe Task Parallelism in SPEC 2006 INT","authors":"Tongxin Bai, C. Ding, Pengcheng Li","doi":"10.1109/CCGrid.2015.159","DOIUrl":"https://doi.org/10.1109/CCGrid.2015.159","url":null,"abstract":"To migrate complex sequential code to multicore, profiling is often used on sequential executions to find opportunities for parallelization. In non-scientific code, the potential parallelism often resides in while-loops rather than for-loops. The do-all model used in the past by many studies cannot detect this type of parallelism. A new, task-based model has been used by a number of recent studies and shown safe for general loops and functions. This paper presents a feedback-based compiler that measures the amount of safe task parallelism in a program and ranks the potential candidates. It solves two problems unique for task analysis. The first is the relation between loop parallelism and function parallelism. The second is the effect of the calling context. The new tool is built in the GCC compiler and used to analyze the entire suite of SPEC 2006 integer benchmarks.","PeriodicalId":6664,"journal":{"name":"2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing","volume":"50 1","pages":"402-411"},"PeriodicalIF":0.0,"publicationDate":"2015-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74255348","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：