Yunfang Tai, Wanwei Cai, Qi Liu, Ge Zhang, Wenzhi Wang
{"title":"Comparisons of Memory Virtualization Solutions for Architectures with Software-Managed TLBs","authors":"Yunfang Tai, Wanwei Cai, Qi Liu, Ge Zhang, Wenzhi Wang","doi":"10.1109/NAS.2013.22","DOIUrl":"https://doi.org/10.1109/NAS.2013.22","url":null,"abstract":"Memory virtualization plays an important role in system virtualization. However, traditional memory virtualization solutions are usually for those architectures with hardware-managed TLBs, such as x86, ARM and so on. The solutions for architectures with software-managed TLBs are rarely mentioned. This paper presents three different memory virtualization solutions for architectures with software-managed TLBs. The difference is that different methods are used to tackle guest TLBs. One is emulating the guest TLBs by software, another is eliminating the guest TLBs and the third is emulating guest TLBs by hardware. After comparisons on hardware platform with MIPS CPUs, it can be seen that the method eliminating guest TLBs can increase the memory bandwidth by more than 100% on average compared to the method emulating guest TLBs by software. After comparisons on simulation platform with MIPS CPUs, it can be seen that the method emulating guest TLBs by hardware would cause about 135% more extra exceptions than the method eliminating guest TLBs. The method eliminating guest TLBs is a good choice when full virtualization is not necessary on the CPUs with software-managed TLBs.","PeriodicalId":213334,"journal":{"name":"2013 IEEE Eighth International Conference on Networking, Architecture and Storage","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121570044","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}
{"title":"A Mechanism of Maintaining the Survivability of Streaming Media Service in Overlay Networks","authors":"Bo Bai, Ji-hong Zhao, Hua Qu","doi":"10.1109/NAS.2013.16","DOIUrl":"https://doi.org/10.1109/NAS.2013.16","url":null,"abstract":"With the quick development of service-oriented network, the services of streaming media and their traffic has become a rather important part in the circumstance of virtual network. However, there hasn't been a unified control mechanism to maintain the qualities of these services. The QoS of streaming media is a great concern of current network, and it'll be vital in future network because of the rapid growth of internet users and traffics. This paper describes a mechanism of maintaining the survivalbility of streaming media service in the circumstance of overlay network. We propose a method to calculate the health value of each path and service. Through this mechanism we can evaluate the current quality of services and provide information for further decisions. As a proof of concept we implement an experimental scenario to assess the functionality and the availability of this mechanism. It has managed effectively in the evaluation of streaming services.","PeriodicalId":213334,"journal":{"name":"2013 IEEE Eighth International Conference on Networking, Architecture and Storage","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126398449","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}
Ping-Hsiu Huang, Guang Wan, Ke Zhou, Miaoqing Huang, Chun-hua Li, Hua Wang
{"title":"Improve Effective Capacity and Lifetime of Solid State Drives","authors":"Ping-Hsiu Huang, Guang Wan, Ke Zhou, Miaoqing Huang, Chun-hua Li, Hua Wang","doi":"10.1109/NAS.2013.13","DOIUrl":"https://doi.org/10.1109/NAS.2013.13","url":null,"abstract":"Flash-based SSDs are becoming increasingly popular in modern storage systems, especially in high-performance computing infrastructures. However, several inherent technical limitations still remain to prevent their widespread deployment. One of the critical concerns is their limited lifetime, which is directly relevant to the total writes experienced by SSDs. In this paper, we present a Content and semantics Aware File System (CSA-FS) which is able to reduce write traffic to SSDs. It employs deduplication and delta-encoding techniques to file system data blocks and semantic blocks, respectively. It is motivated by two important observations: (1) there exists a huge amount of content redundancy within primary storage systems, and (2) semantic blocks are visited much more frequently than data blocks, with each update bringing very minimal changes. By separately deduplicating redundant data blocks and delta-encoding similar semantic blocks, CSA-FS can significantly reduce the total write traffic to SSDs and greatly improve their lifetime correspondingly, at an acceptable cost of at most 7% performance degradation across a variety of workloads.","PeriodicalId":213334,"journal":{"name":"2013 IEEE Eighth International Conference on Networking, Architecture and Storage","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124894831","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}
{"title":"A New Metadata Update Method for Fast Recovery of SSD Cache","authors":"J. Yang, Q. Yang","doi":"10.1109/NAS.2013.14","DOIUrl":"https://doi.org/10.1109/NAS.2013.14","url":null,"abstract":"In order to maintain data in an SSD (solid-state disk) cache durable after a crash or reboot, metadata information needs to be stored persistently in SSD. There are two typical metadata methods, update-write-update and write-update. While write-update method has one less SSD write operation than update-write-update for each write I/O, it limits the amount of cached data that can be used after a system crash. We present a design and implementation of a novel metadata update method for SSD cache, referred to as Lazy-Update Following an Update-Write (LUFUW). Our new metadata update method allows maximal amount of data in SSD cache available upon restart after a power failure or system crash with minimal additional writes to SSD. This capability makes restart run twice as fast as existing SSD caches such as Flash cache [1] that can only use dirty data in the cache after crash recovery. We present our prototype implementation on Linux kernel and performance measurements as compared with existing SSD cache solutions.","PeriodicalId":213334,"journal":{"name":"2013 IEEE Eighth International Conference on Networking, Architecture and Storage","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129978822","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}
Yuan Tian, S. Klasky, Weikuan Yu, Bin Wang, H. Abbasi, N. Podhorszki, R. Grout
{"title":"DynaM: Dynamic Multiresolution Data Representation for Large-Scale Scientific Analysis","authors":"Yuan Tian, S. Klasky, Weikuan Yu, Bin Wang, H. Abbasi, N. Podhorszki, R. Grout","doi":"10.1109/NAS.2013.21","DOIUrl":"https://doi.org/10.1109/NAS.2013.21","url":null,"abstract":"Fast growing large-scale systems enable scientific applications to run at a much larger scale and accordingly produce gigantic volumes of simulation output. Such data imposes a grand challenge to post-processing tasks such as visualization and data analysis, because these tasks are often performed at a host machine that is remotely located and equipped with much less memory and storage resources. During the simulation runs, it is also desirable for scientists to be able to interactively monitor and steer the progress of simulation. This requires scientific data to be represented in an efficient form for initial exploration and computation steering. In this paper, we propose DynaM a software framework that can represent scientific data in a multiresolution form, and dynamically organize data blocks into an optimized layout for efficient scientific analysis. DynaM supports a convolution-based multiresolution data representation for abstracting scientific data for visualization at a wide spectrum of resolution. To support the efficient generation and retrieval of different data granularities from such representation, a dynamic data organization in DynaM is enabled to cater distinct peculiarities of different size data blocks for efficient and balanced I/O performance. Our experimental results demonstrate that DynaM can efficiently represent large scientific dataset and speed up the visualization of multidimensional scientific data. An up to 29 times speedup is achieved on Jaguar supercomputer at Oak Ridge National Laboratory.","PeriodicalId":213334,"journal":{"name":"2013 IEEE Eighth International Conference on Networking, Architecture and Storage","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130156569","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}
{"title":"BFEPM: Best Fit Energy Prediction Modeling Based on CPU Utilization","authors":"Xiao Zhang, Jian-Jun Lu, X. Qin","doi":"10.1109/NAS.2013.12","DOIUrl":"https://doi.org/10.1109/NAS.2013.12","url":null,"abstract":"Energy cost becomes a major part of data center operational cost. Computer system consume more power when it runs under high workload. Many past studies focused on how to predict power consumption by performance counters. Some models retrieve performance counters from chips. Some models query performance counters from OS. Most of these researches were verified on several machines and claimed their models were accurate under the test. We found different servers have different energy consumption characters even with same CPU. In this paper, we present BFEPM, a best fit energy prediction model. It choose best model based on the power consumption benchmark result. We illustrate how to use benchmark result to find a best fit model. Then we validate the viability and effectiveness of model on all published results. At last, we apply the best fit model on two different machines to estimate the real-time energy consumption. The results show our model can get better results than single model.","PeriodicalId":213334,"journal":{"name":"2013 IEEE Eighth International Conference on Networking, Architecture and Storage","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127677702","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}
Xunfei Jiang, Ji Zhang, Mohammed I. Alghamdi, X. Qin, Minghua Jiang
{"title":"PEAM: Predictive Energy-Aware Management for Storage Systems","authors":"Xunfei Jiang, Ji Zhang, Mohammed I. Alghamdi, X. Qin, Minghua Jiang","doi":"10.1109/NAS.2013.20","DOIUrl":"https://doi.org/10.1109/NAS.2013.20","url":null,"abstract":"This paper presents a novel Predictive Energy-Aware Management (PEAM) system that is able to reduce the energy costs of storage systems by appropriately selecting data transmission methods. In particular, we evaluate the energy costs of three methods (1. transfer data without archiving and compression, 2. archive and transfer data, 3. compress and transfer data) in preliminary experiments. According to the results, we observe that the energy consumption of data transmission greatly varies case by case. We cannot simply apply one method in all cases. Therefore, we design an energy prediction model that can estimate the total energy cost of data transmission by using particular transmission methods. Based on the model, our predictive energy-aware management system can automatically select the most energy efficient method for data transmission. Our experimental results show that our system performs better than simply selecting any one among the three methods for data transmission in terms of energy efficiency.","PeriodicalId":213334,"journal":{"name":"2013 IEEE Eighth International Conference on Networking, Architecture and Storage","volume":"29 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120973413","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}
{"title":"Chariot: A High Compatible Architecture to Improve Virtual Machine Reliability","authors":"Haoquiang Zheng, Xiaoshe Dong, Endong Wang, Baoke Chen, Weifeng Gong, Xingjun Zhang","doi":"10.1109/NAS.2013.23","DOIUrl":"https://doi.org/10.1109/NAS.2013.23","url":null,"abstract":"Currently, the virtualization technologies can integrate multiple operating systems into a high-performance server to maximize the utilization of the server's resources. This server can serves more users. However, the driver faults in virtual machine still seriously affect the reliability of the virtual machine, and even affect the reliability of the entire server. This paper presents Chariot, a high compatible architecture to improve virtual machine reliability. If the driver is loaded by the Chariot's isolation loading mechanism, its memory usage will be timely monitored by Chariot, and its access control table will be established. Through setting the corresponding shadow page table of the whole kernel space of the virtual machine, Chariot captures the write operations of the isolated driver. Combing the access control table, Chariot can determine the correctness of these writing operations. Chariot has an effective errors isolation capability, and is easy to develop. Also Chariot has an excellent compatibility and needs not to modify the drivers and the operation system in the virtual machine. Experimental results show that Chariot can effectively isolate the driver faults, and improve the reliability of operation system in the virtual machine environments.","PeriodicalId":213334,"journal":{"name":"2013 IEEE Eighth International Conference on Networking, Architecture and Storage","volume":"234 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121245315","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}
{"title":"High-Speed Multicast Scheduling for All-Optical Packet Switches","authors":"Zhiyang Guo, Yuanyuan Yang","doi":"10.1109/NAS.2013.26","DOIUrl":"https://doi.org/10.1109/NAS.2013.26","url":null,"abstract":"In this paper, we study multicast scheduling in all-optical packet switches. We first propose a novel optical buffer called multicast-enabled Fiber-Delay-Lines (M-FDLs), which can provide flexible delay for copies of multicast packets using only a small number of FDL segments. We then present a Delay-Guaranteed Multicast Scheduling (DGMS) algorithm that considers the schedule of each arriving packet for multiple time slots. We show that DGMS has several desirable features, such as guaranteed delay upper bound and adaptivity to transmission requirements. To relax the time constraint of DGMS, we further propose a parallel and pipeline architecture for DGMS that distributes the scheduling task to multiple pipelined processing stages, with N processors in each stage, where N is the switch size. Finally, by using a simple combination logic circuit, we show that each processor can finish the scheduling for one time slot in O(1) time. The performance of DGMS is tested extensively against statistical traffic models and real Internet traffic, and the results show that the proposed DGMS algorithm can achieve ultra-low average packet delay with minimum packet drop ratio.","PeriodicalId":213334,"journal":{"name":"2013 IEEE Eighth International Conference on Networking, Architecture and Storage","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132750251","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}
Longjiang Guo, Shufang Du, Meirui Ren, Yu Liu, Jinbao Li, J. He, Ning Tian, Keqin Li
{"title":"Parallel Algorithm for Approximate String Matching with K Differences","authors":"Longjiang Guo, Shufang Du, Meirui Ren, Yu Liu, Jinbao Li, J. He, Ning Tian, Keqin Li","doi":"10.1109/NAS.2013.40","DOIUrl":"https://doi.org/10.1109/NAS.2013.40","url":null,"abstract":"Approximate string matching using the k-difference technique has been widely applied to many fields such as pattern recognition and computational biology. Data dependency exists in the traditional sequential algorithm. Therefore, it is hard to design a parallel algorithm for approximate string matching with k differences. This paper presents a technique to eliminate data dependency. Based on this technique, this paper also presents a parallel algorithm which can calculate the elements in the same row of the edit distance matrix in parallel by eliminating data dependency. The algorithm has high parallelism, but requires synchronization. To validate the proposed algorithm, it is implemented on GPU and multiple-core CPUs. Moreover, the CUDA optimization techniques are also presented in the paper. Finally, experimental results show that, compared with the traditional sequential algorithm on CPU with twenty-four cores, the proposed parallel algorithm achieves speedup of 7-42 on GPU.","PeriodicalId":213334,"journal":{"name":"2013 IEEE Eighth International Conference on Networking, Architecture and Storage","volume":"230 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121924502","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}