High-performance network and channel-based storage

R.H. Katz
1992 Proceedings of the IEEE  
In the traditional mainframe-centered view of a computer system, storage devices are coupled to the system through complex hardware subsystems called I/O channels. With the dramatic shift towards workstation-based computing, and its associated client/server model of computation, storage facilities are now found attached to file servers and distributed throughout the network. In this paper, we discuss the underlying technology trends that are leading to high performance network-based storage,
more » ... ely advances in networks, storage devices, and I/O controller and server architectures. We review several commercial systems and research prototypes that are leading to a new approach to high performance computing based on network-attached storage. Admittedly, centralized storage also has its weaknesses. A server or network failure renders the client workstations unusable and the network represents the critical performance bottleneck. A highly tuned remote file system on a 10 megabit (Mbit) per second Ethernet can provide perhaps 500K bytes per second to remote client applications. Sixty 8K byte 1/Os per second would fully utilize this bandwidth. Obtaining the right balance of workstations to servers depends on their relative processing power, the amount of memory dedicated to file caches on workstations and servers, the available network bandwidth, and the I/O bandwidth of the server. It is interesting to note that today's servers are not I/O limited: the Ethernet bandwidth can be fully utilized by the I/O bandwidth of only two magnetic disks! Meanwhile, other technology developments in processors, networks, and storage systems are affecting the relationship between clients to servers. It is well known that processor performance, as measured in MIPS ratings, is increasing at an astonishing rate, doubling on the order of once every eighteen months to two years. The newest generation of RISC processors have performance in the 50 to 60 MIPS range. For example, a recent workstation announced by Hewlett-Packard Corporation, the HP 9000/730, has been rated at 72 SPECMarks (1 SPECMark is roughly the processing power of a single Digital Equipment Corporation VAX 11/780 on a particular benchmark set). Powerful shared memory multiprocessor systems, now available from companies such as Silicon Graphics and Solbome, provide well over 100 MIPS performance. One of Amdahl's famous laws equated one MIPS of processing power with one megabit of I/O per second. Obviously such processing rates far exceed anything that can be delivered by existing server, network, or storage architectures. Unlike processor power, network technology evolves at a slower rate, but when it advances, it does so in order of magnitude steps. In the last decade we have advanced from 3 Mbit/second Ethernet to 10 Mbit/second Ethernet. We are now on the verge of a new generation of network technology, based on fiber optic interconnect, called FDDI. This technology promises 100 Mbits per second, and at least initially, it will move the server bottleneck from the network to the server CPU or its storage system. With more powerful processors available on the horizon, the performance challenge is very likely to be in the storage system, where a typical magnetic disk can service thirty 8K byte I/Os per second and can sustain a data rate in the range of 1 to 3 MBytes per second. And even faster networks and interconnects, in the gigabit range, are now commercially available and will become more widespread as their costs begin to drop [UltraNet 90]. To keep up with the advances in processors and networks, storage systems are also experiencing rapid improvements. Magnetic disks have been doubling in storage capacity once every three years. As disk form factors shrink from 14" to 3.5" and below, the disks can be made to spin faster, thus increasing the sequential transfer rate. Unfortunately, the random I/O rate is improving only very slowly, due to mechanically-limited positioning delays. Since I/O and data rates are primarily disk actuator limited, a new storage system approach called disk arrays addresses this problem by replacing a small number of large format disks by a very large number of small format disks. Disk arrays maintain the high capacity of the storage system, while enormously increasing the system's disk actuators and thus the aggregate I/O and data rate. The confluence of developments in processors, networks, and storage offers the possibility of extending the client-server model so effectively used in workstation environments to higher performance environments, which integrate supercomputer, near supercomputers, workstations, and storage services on a very high performance network. The technology is rapidly reaching the point where it is possible to think in terms of diskless supercomputers in much the same way as we think about diskless workstations. Thus, the network is emerging as the future "backplane" of high performance systems. The challenge is to develop the new hardware and software architec-High Performance Nawoik <nd Channel-B««ed Storage September 27,1991 2 tures that will be suitable for this world of network-based storage. The emphasis of this paper is on the integration of storage and network services, and the challenges of managing the complex storage hierarchy of the future: file caches, on-line disk storage, near-line data libraries, and off-line archives. We specifically ignore existing mainframe I/O architectures, as these are well described elsewhere (for example, in [Hennessy 90]. The rest of this paper is organized as follows. In the next three sections, we will review the recent advances in interconnect, storage devices, and distributed software, to better understand the underlying changes in network, storage, and software technologies. Section 5 contains detailed case studies of commercially available high performance networks, storage servers, and file servers, as well as a prototype high performance network-attached I/O controller being developed at the University of California, Berkeley. Our summary, conclusions, and suggestions for future research are found in Section 6.
doi:10.1109/5.158597 fatcat:jm7thtxk6bfoxiyckb3s3h7cre