@InProceedings{barve:competitive2,
  author = {Rakesh Barve and Mahesh Kallahalla and Peter J. Varman and Jeffrey
  Scott Vitter},
  title = {Competitive Parallel Disk Prefetching and Buffer Management},
  booktitle = {Proceedings of the Fifth Workshop on Input/Output in Parallel
  and Distributed Systems},
  year = {1997},
  month = {November},
  pages = {47--56},
  publisher = {ACM Press},
  address = {San Jose, CA},
  keyword = {disk prefetching, file caching, parallel I/O, pario-bib},
  abstract = {We provide a competitive analysis framework for online
  prefetching and buffer management algorithms in parallel I/O systems, using a
  read-once model of block references. This has widespread applicability to key
  I/O-bound applications such as external merging and concurrent playback of
  multiple video streams. Two realistic lookahead models, global lookahead and
  local lookahead, are defined. Algorithms NOM and GREED based on these two
  forms of lookahead are analyzed for shared buffer and distributed buffer
  configurations, both of which occur frequently in existing systems. An
  important aspect of our work is that we show how to implement both the models
  of lookahead in practice using the simple techniques of forecasting and
  flushing. \par Given a D-disk parallel I/O system and a globally shared I/O
  buffer that can hold upto M disk blocks, we derive a lower bound of
  $\Omega(\sqrt{D}$) on the competitive ratio of any deterministic online
  prefetching algorithm with O(M) lookahead. NOM is shown to match the lower
  bound using global M-block lookahead. In contrast, using only local lookahead
  results in an $\Omega(D)$ competitive ratio. When the buffer is distributed
  into D portions of M/D blocks each, the algorithm GREED based on local
  lookahead is shown to be optimal, and NOM is within a constant factor of
  optimal. Thus we provide a theoretical basis for the intuition that global
  lookahead is more valuable for prefetching in the case of a shared buffer
  configuration whereas it is enough to provide local lookahead in case of the
  distributed configuration. Finally, we analyze the performance of these
  algorithms for reference strings generated by a uniformly-random stochastic
  process and we show that they achieve the minimal expected number of I/Os.
  These results also give bounds on the worst-case expected performance of
  algorithms which employ randomization in the data layout.},
  comment = {See barve:competitive.}
}

@InProceedings{chang:reuse,
  author = {Tai-Sheng Chang and Sangyup Shim and David H.~C. Du},
  title = {The Scalability of Spatial Reuse Based Serial Storage Interfaces},
  booktitle = {Proceedings of the Fifth Workshop on Input/Output in Parallel
  and Distributed Systems},
  year = {1997},
  month = {November},
  pages = {93--101},
  publisher = {ACM Press},
  address = {San Jose, CA},
  keyword = {I/O interface, I/O network, I/O architecture, parallel I/O,
  pario-bib},
  abstract = {Due to the growing popularity of emerging applications such as
  digital libraries, Video-On Demand, distance learning, and Internet
  World-Wide Web, multimedia servers with a large capacity and high performance
  storage subsystem are in high demand. Serial storage interfaces are emerging
  technologies designed to improve the performance of such storage subsystems.
  They provide high bandwidth, fault tolerance, fair bandwidth sharing and long
  distance connection capability. All of these issues are critical in designing
  a scalable and high performance storage subsystem. Some of the serial storage
  interfaces provide the spatial reuse feature which allows multiple concurrent
  transmissions. That is, multiple hosts can access disks concurrently with
  full link bandwidth if their access paths are disjoint. Spatial reuse
  provides a way to build a storage subsystem whose aggregate bandwidth may be
  scaled up with the number of hosts. However, it is not clear how much the
  performance of a storage subsystem could be improved by the spatial reuse
  with different configurations and traffic scenarios. Both limitation and
  capability of this scalability need to be investigated. To understand their
  fundamental performance characteristics, we derive an analytic model for the
  serial storage interfaces with the spatial reuse feature. Based on this
  model, we investigate the maximum aggregate throughput from different system
  configurations and load distributions. We show how the number of disks needed
  to saturate a loop varies with different number of hosts and different load
  scenarios. We also show how the load balancing by uniformly distributing the
  load to all the disks on a loop may incur high overhead. This is because the
  accesses to far away disks need to go through many links and consume the
  bandwidth of each link it goes through. The results show the achievable
  throughput may be reduced by more than half in some cases.}
}

@InProceedings{cho:local,
  author = {Yong Cho and Marianne Winslett and Mahesh Subramaniam and Ying Chen
  and Szu-wen Kuo and Kent E. Seamons},
  title = {Exploiting Local Data in Parallel Array {I/O} on a Practical Network
  of Workstations},
  booktitle = {Proceedings of the Fifth Workshop on Input/Output in Parallel
  and Distributed Systems},
  year = {1997},
  month = {November},
  pages = {1--13},
  publisher = {ACM Press},
  address = {San Jose, CA},
  keyword = {parallel I/O, distributed system, pario-bib},
  abstract = {A cost-effective way to run a parallel application is to use
  existing workstations connected by a local area network such as Ethernet or
  FDDI. In this paper, we present an approach for parallel I/O of
  multidimensional arrays on small networks of workstations with a shared-media
  interconnect, using the Panda I/O library. \par In such an environment, the
  message passing throughput per node is lower than the throughput obtainable
  from a fast disk and it is not easy for users to determine the configuration
  which will yield the best I/O performance. \par We introduce an I/O strategy
  that exploits local data to reduce the amount of data that must be shipped
  across the network, present experimental results, and analyze the results
  using an analytical performance model and predict the best choice of I/O
  parameters. \par Our experiments show that the new strategy results in a
  factor of 1.2--2.1 speedup in response time compared to the Panda version
  originally developed for the IBM SP2, depending on the array sizes,
  distributions and compute and I/O node meshes. Further, the performance model
  predicts the results within a 13\% margin of error.}
}

@InProceedings{cormen:fft3,
  author = {Thomas H. Cormen and Jake Wegmann and David M. Nicol},
  title = {Multiprocessor Out-of-Core {FFTs} with Distributed Memory and
  Parallel Disks},
  booktitle = {Proceedings of the Fifth Workshop on Input/Output in Parallel
  and Distributed Systems},
  year = {1997},
  month = {November},
  pages = {68--78},
  publisher = {ACM Press},
  address = {San Jose, CA},
  keyword = {out of core, parallel I/O, pario-bib},
  abstract = {This paper extends an earlier out-of-core Fast Fourier Transform
  (FFT) method for a uniprocessor with the Parallel Disk Model (PDM) to use
  multiple processors. Four out-of-core multiprocessor methods are examined.
  Operationally, these methods differ in the size of "mini-butterfly" computed
  in memory and how the data are organized on the disks and in the distributed
  memory of the multiprocessor. The methods also perform differing amounts of
  I/O and communication. Two of them have the remarkable property that even
  though they are computing the FFT on a multiprocessor, all interprocessor
  communication occurs outside the mini-butterfly computations; communication
  that ordinarily occurs in a butterfly is folded into other data-movement
  operations. An analysis program shows that the two methods that use no
  butterfly communication usually use less communication overall than the other
  methods. The analysis program is fast enough that it can be invoked at run
  time to determine which of the four methods uses the least communication. One
  set of performance results on a small workstation cluster indicates that the
  methods without butterfly communication are approximately 9.5\% faster.
  Moreover, they are much easier to implement.},
  comment = {See also cormen:fft and cormen:fft2.}
}

@InProceedings{cortes:cooperative,
  author = {Toni Cortes and Sergi Girona and Jes\'us Labarta},
  title = {Design Issues of a Cooperative Cache with no Coherence Problems},
  booktitle = {Proceedings of the Fifth Workshop on Input/Output in Parallel
  and Distributed Systems},
  year = {1997},
  month = {November},
  pages = {37--46},
  publisher = {ACM Press},
  address = {San Jose, CA},
  keyword = {cooperative caching, distributed file system, parallel I/O,
  pario-bib},
  abstract = {In this paper, we examine some of the important problems observed
  in the design of cooperative caches. Solutions to the coherence,
  load-balancing and fault-tolerance problems are presented. These solutions
  have been implemented as a part of PAFS, a parallel/distributed file system,
  and its performance has been compared to the one achieved by xFS. Using the
  comparison results, we have observed that the proposed ideas not only solve
  the main problems of cooperative caches, but also increase the overall system
  performance. Although the solutions presented in this paper were targeted to
  a parallel machine, reasonable good results have also been obtained for
  networks of workstations.}
}

@InProceedings{foster:remote-io,
  author = {Ian Foster and David {Kohr, Jr.} and Rakesh Krishnaiyer and Jace
  Mogill},
  title = {Remote {I/O}: Fast Access to Distant Storage},
  booktitle = {Proceedings of the Fifth Workshop on Input/Output in Parallel
  and Distributed Systems},
  year = {1997},
  month = {November},
  pages = {14--25},
  publisher = {ACM Press},
  address = {San Jose, CA},
  keyword = {parallel I/O, distributed file system, pario-bib},
  abstract = {As high-speed networks make it easier to use distributed
  resources, it becomes increasingly common that applications and their data
  are not colocated. Users have traditionally addressed this problem by
  manually staging data to and from remote computers. We argue instead for a
  remote I/O paradigm in which programs use familiar parallel I/O interfaces to
  access remote filesystems. In addition to simplifying remote execution,
  remote I/O can improve performance relative to staging by overlapping
  computation and data transfer or by reducing communication requirements.
  However, remote I/O also introduces new technical challenges in the areas of
  portability, performance, and integration with distributed computing systems.
  We propose techniques designed to address these challenges and describe a
  remote I/O library called RIO that we are developing to evaluate the
  effectiveness of these techniques. RIO addresses issues of portability by
  adopting the quasi-standard MPI-IO interface and by defining a RIO device and
  RIO server within the ADIO abstract I/O device architecture. It addresses
  performance issues by providing traditional I/O optimizations such as
  asynchronous operations and through implementation techniques such as
  buffering and message forwarding to offload communication overheads.
  Microbenchmarks and application experiments demonstrate that our techniques
  can improve turnaround time relative to staging.}
}

@InProceedings{kandemir:locality,
  author = {M. Kandemir and A. Choudhary and J. Ramanujam and M. Kandaswamy},
  title = {A Unified Compiler Algorithm for Optimizing Locality, Parallelism,
  and Communication in Out-of-Core Computations},
  booktitle = {Proceedings of the Fifth Workshop on Input/Output in Parallel
  and Distributed Systems},
  year = {1997},
  month = {November},
  pages = {79--92},
  publisher = {ACM Press},
  address = {San Jose, CA},
  keyword = {compiler, out of core, parallel I/O, pario-bib},
  abstract = {This paper presents compiler algorithms to optimize out-of-core
  programs. These algorithms consider loop and data layout transformations in a
  unified framework. The performance of an out-of-core loop nest containing
  many references can be improved by a combination of restructuring the loops
  and file layouts. This approach considers array references one-by-one and
  attempts to optimize each reference for parallelism and locality. When there
  are references for which parallelism optimizations do not work, communication
  is vectorized so that data transfer can be performed before the innermost
  tiling loop. Preliminary results from hand-compiles on IBM SP-2 and Intel
  Paragon show that this approach reduces the execution time, improves the
  bandwidth speedup and overall speedup. In addition, we extend the base
  algorithm to work with file layout constraints and show how it can be used
  for optimizing programs consisting of multiple loop nests.}
}

@Article{kandemir:optimizing,
  author = {M. Kandemir and A. Choudhary and J. Ramanujam and R. Bordawekar},
  title = {Optimizing Out-of-core Computations in Uniprocessors},
  journal = {Newsletter of the Technical Committee on Computer Architecture
  (TCCA)},
  year = {1997},
  month = {June},
  pages = {25--27},
  keyword = {out of core, parallel I/O, pario-bib}
}

@InProceedings{madhyastha:classification,
  author = {Tara M. Madhyastha and Daniel A. Reed},
  title = {Input/Output Access Pattern Classification Using Hidden {Markov}
  Models},
  booktitle = {Proceedings of the Fifth Workshop on Input/Output in Parallel
  and Distributed Systems},
  year = {1997},
  month = {November},
  pages = {57--67},
  publisher = {ACM Press},
  address = {San Jose, CA},
  keyword = {workload characterization, file access pattern, parallel I/O,
  pario-bib},
  abstract = {Input/output performance on current parallel file systems is
  sensitive to a good match of application access pattern to file system
  capabilities. Automatic input/output access classification can determine
  application access patterns at execution time, guiding adaptive file system
  policies. In this paper we examine a new method for access pattern
  classification that uses hidden Markov models, trained on access patterns
  from previous executions, to create a probabilistic model of input/output
  accesses. We compare this approach to a neural network classification
  framework, presenting performance results from parallel and sequential
  benchmarks and applications.}
}

@InBook{mpi2-io,
  author = {{Message-Passing Interface Forum}},
  title = {{MPI-2.0}: Extensions to the Message-Passing Interface},
  chapter = {9},
  year = {1997},
  month = {June},
  publisher = {MPI Forum},
  URL = {http://www.mpi-forum.org/docs/docs.html},
  keyword = {MPI, message passing, parallel computing, library, parallel I/O,
  pario-bib},
  comment = {Chapter 9 is about I/O extensions.}
}

@InProceedings{prabhakar:browsing,
  author = {Sunil Prabhakar and Divyakant Agrawal and Amr {El Abbadi} and Ambuj
  Singh and Terence Smith},
  title = {Browsing and Placement of Multiresolution Images on Parallel Disks},
  booktitle = {Proceedings of the Fifth Workshop on Input/Output in Parallel
  and Distributed Systems},
  year = {1997},
  month = {November},
  pages = {102--113},
  publisher = {ACM Press},
  address = {San Jose, CA},
  keyword = {multimedia, parallel I/O, pario-bib},
  abstract = {With rapid advances in computer and communication technologies,
  there is an increasing demand to build and maintain large image repositories.
  In order to reduce the demands on I/O and network resources, multiresolution
  representations are being proposed for the storage organization of images.
  Image decomposition techniques such as {\em wavelets} can be used to provide
  these multiresolution images. The original image is represented by several
  coefficients, one of them with visual similarity to the original image, but
  at a lower resolution. These visually similar coefficients can be thought of
  as {\em thumbnails} or {\em icons} of the original image. This paper
  addresses the problem of storing these multiresolution coefficients on disks
  so that thumbnail browsing as well as image reconstruction can be performed
  efficiently. Several strategies are evaluated to store the image coefficients
  on parallel disks. These strategies can be classified into two broad classes
  depending on whether the access pattern of the images is used in the
  placement. Disk simulation is used to evaluate the performance of these
  strategies. Simulation results are validated with results from experiments
  with real disks and are found to be in good agreement. The results indicate
  that significant performance improvements can be achieved with as few as four
  disks by placing image coefficients based upon browsing access patterns.}
}