U. Glaeser

need for fast transfers, up to 1 Gbits/s, of large amounts of information. Other emerging interconnect
standards include the switched InfiniBand architecture, a synthesis of formerly competing System I/O
and NextGeneration I/O proposals, with projected peak bidirectional rates of up to 6 GB/s [30].
Another trend in I/O organizations is the decentralization of storage devices [24,45]. Storage area
networks (SAN) and network-attached storage devices (NASD) are two such directions towards reducing
the tight coupling between servers and devices in traditional I/O architectures. In a SAN, multiple servers
and devices are connected together by a dedicated high-speed network different from, and in addition
to, the local area network (LAN) connecting the servers and clients. Data transfer between a server and
a device occurs over this dedicated back-end network. Networked storage architectures have several
potential benefits. They facilitate sharing of disk-resident data between multiple servers by avoiding the
three-step process (read I/O, network transfer, write I/O) required in transferring data on traditional
server-hosted I/O architectures. Furthermore, they permit autonomous data transfer between devices
simplifying backup and data replication for performance or reliability, and encourage the spatial distribution
of devices on the network, while maintaining the capability for centralized management. A
network-attached storage device [26] allows many of the server functions to be offloaded directly to the
device. Once a request is authenticated by the server and forwarded to the device, data transfer to the network
proceeds independently without further involvement of the server. In principle a NASD can be directly
connected to the LAN or may serve as an independent module in a back-end SAN.
Highly parallel I/O organizations with high-bandwidth interconnections that have the capability of
supporting hundreds of concurrent I/O transfers are a characteristic of current and evolving I/O architectures.
The physical realization in terms of interconnection and communication protocols, redundancy
and fault-tolerance, and balance between distribution and centralization of resources are a continuing
topic of current research. Complex issues dealing with cost, performance, reliability, interoperability,
security, and ease of configuration and management will need to be resolved, with perhaps different
configurations suitable in different application domains.
Whatever the physical manifestation, managing hundreds of concurrent I/O devices in order to fully
exploit their inherent parallelism and high interconnection bandwidth is a challenging problem. To study
the issues at a high level, configuration-independent abstract models such as the parallel disk model (PDM)
[58] have been proposed. Two extremes of logical I/O organizations based on the memory buffer can be
identified: in a shared-buffer organization there is a centralized memory buffer shared by all the disks,
and all accesses are routed through the buffer. In a distributed-buffer organization each disk has a private
buffer used exclusively to buffer data from that disk. The shared configuration has the potential to make
better use of the buffer space by dynamically changing the portion of the buffer devoted to any disk based
on the load. In contrast, the performance of the distributed configuration can be limited by a few heavily
loaded disks. Hybrid configurations are possible as in a logically shared but physically partitioned buffer.
Such an architecture provides the scalability and modularity inherent in having distributed resources
while providing increased resource utilization due to sharing.
33.3 Performance Model for Parallel I/O
Parallel I/O systems have the potential to improve I/O performance if one can exploit disk parallelism by
performing multiple concurrent I/Os; however, it is a challenging problem to successfully exploit the
available disk bandwidth to reduce application I/O latency. According to increasing evidence, traditional disk
management strategies can severely under-utilize available bandwidth and therefore do not scale well, leading
to excessive I/O service time. As a consequence, several new algorithms for managing parallel I/O resources,
with the explicit intention of exploiting I/O parallelism have been recently advanced [5,11,32–36,50,57].
The performance of a parallel I/O system is fundamentally determined by the pattern of disk accesses.
The simplest form of data access, sequential reading of a file, represents the canonical application that can
benefit from parallel I/O. Disk striping provides the natural solution for such an access pattern. The file is
broken into blocks, and the blocks are placed in a round-robin fashion on the D disks, so that every Dth
block is placed on the same disk. A main memory buffer of D blocks is used. In each I/O an entire stripe
© 2002 by CRC Press LLC