Making the Most out of Direct-Access Network Attached Storage

The performance of high-speed network-attached storage applications is often limited by end-system overhead, caused primarily by memory copying and network protocol processing. In this paper, we examine alternative strategies for reducing overhead in such systems. We consider optimizations to remote procedure call (RPC)-based data transfer using either remote direct memory access (RDMA) or network interface support for pre-posting of application receive buffers. We demonstrate that both mechanisms enable file access throughput that saturates a 2Gb/s network link when performing large I/Os on relatively slow, commodity PCs. However, for multi-client workloads dominated by small I/Os, throughput is limited by the per-I/O overhead of processing RPCs in the server. For such workloads, we propose the use of a new network I/O mechanism, Optimistic RDMA (ORDMA). ORDMA is an alternative to RPC that aims to improve server throughput and response time for small I/Os. We measured performance improvements of up to 32% in server throughput and 36% in response time with use of ORDMA in our prototype.Engineering and Applied Science

The End of Slow Networks: It's Time for a Redesign

Next generation high-performance RDMA-capable networks will require a fundamental rethinking of the design and architecture of modern distributed DBMSs. These systems are commonly designed and optimized under the assumption that the network is the bottleneck: the network is slow and "thin", and thus needs to be avoided as much as possible. Yet this assumption no longer holds true. With InfiniBand FDR 4x, the bandwidth available to transfer data across network is in the same ballpark as the bandwidth of one memory channel, and it increases even further with the most recent EDR standard. Moreover, with the increasing advances of RDMA, the latency improves similarly fast. In this paper, we first argue that the "old" distributed database design is not capable of taking full advantage of the network. Second, we propose architectural redesigns for OLTP, OLAP and advanced analytical frameworks to take better advantage of the improved bandwidth, latency and RDMA capabilities. Finally, for each of the workload categories, we show that remarkable performance improvements can be achieved

On-Disk Data Processing: Issues and Future Directions

In this paper, we present a survey of "on-disk" data processing (ODDP). ODDP, which is a form of near-data processing, refers to the computing arrangement where the secondary storage drives have the data processing capability. Proposed ODDP schemes vary widely in terms of the data processing capability, target applications, architecture and the kind of storage drive employed. Some ODDP schemes provide only a specific but heavily used operation like sort whereas some provide a full range of operations. Recently, with the advent of Solid State Drives, powerful and extensive ODDP solutions have been proposed. In this paper, we present a thorough review of architectures developed for different on-disk processing approaches along with current and future challenges and also identify the future directions which ODDP can take.Comment: 24 pages, 17 Figures, 3 Table

Bridges Structural Health Monitoring and Deterioration Detection Synthesis of Knowledge and Technology

INE/AUTC 10.0

What can AI do for you?

Simply put, most organizations do not know how to approach the incorporation of AI into their businesses, and few are knowledgeable enough to understand which concepts are applicable to their business models. Doing nothing and waiting is not an option: Mahidar and Davenport (2018) argue that companies that try to play catch-up will ultimately lose to those who invested and began learning early. But how do we bridge the gap between skepticism and adoption? We propose a toolkit, inclusive of people, processes, and technologies, to help companies with discovery and readiness to start their AI journey. Our toolkit will deliver specific and actionable answers to the operative question: What can AI do for you