I/O is quickly emerging as the main bottleneck limiting performance in modern day clusters. The need for scalable parallel I/O and file systems is becoming more and more urgent. In this paper, we examine the feasibility of leveraging InfiniBand technology to improve I/O performance and scalability of cluster file systems. We use Parallel Virtual File System (PVFS) as a basis for exploring these features. In this

The advent of networking technologies and high performance transport protocols facilitates the service of storage over networks. However, they pose challenges in integration and interaction among storage server application components and system components. In this paper, we put forward a component, called Unifier, to provide more efficient integration and better interaction among these components. Unifier has three notable features. (1) Unifier integrates cache management and communication buffer management. It offers a single copy data sharing among all components in a server application safely and concurrently. (2) It reduces memory registration and deregistration costs to enable applications to take full advantage of RDMA operations. (3) It provides means to achieve adaptation, application-specific optimization, and better cooperation among different components. This paper presents the design and implementation of Unifier. This component has been deployed and evaluated in a version of PVFS1 implementation over InfiniBand. Experimental results show performance improvements between 30 % and 70 % over other approaches. Better scalability is also achieved by the PVFS I/O servers.

storage area

We propose a unified, low-overhead framework (ULF) to support continuous system profiling and optimization based on a specifically designed embedded board. Instead of building a new profiling tool from scratch, ULF provides a unified interface to integrate various existing profiling tools and optimizers, and helps to easily build future tools. ULF uses an embedded processor to offload tasks of post-processing profiling data, which reduces system overhead caused by profiling tools and makes ULF especially suitable for continuous profiling on production systems. By processing the profiling data in parallel and providing feedback promptly, ULF supports on-line optimization. Our case study on I/O profiling demonstrated that ULFenhanced profiling tool dramatically reduces overhead making continuous profiling on production systems feasible. Key words: Embedded system, continuous profiling, on-line optimization, performance evaluation 1

I/O is quickly emerging as the main bottleneck limiting performance in modern day clusters. The need for scalable parallel I/O and file systems is becoming more and more urgent. In this paper, we examine the feasibility of leveraging InfiniBand technologies to improve I/O performance and scalability of cluster file systems. We use PVFS as a basis for exploring these features. We design