BibTeX for papers by David Kotz; for complete/updated list see
https://www.cs.dartmouth.edu/~kotz/research/papers.html

@Article{kotz:jdapple,
  author =        {David Kotz},
  title =         {{A DAta-Parallel Programming Library for Education (DAPPLE)}},
  journal =       {Computer Science Education},
  year =          1996,
  volume =        6,
  number =        2,
  pages =         {141--159},
  publisher =     {Ablex Publishing},
  copyright =     {Ablex Publishing},
  DOI =           {10.1080/0899340950060203},
  URL =           {https://www.cs.dartmouth.edu/~kotz/research/kotz-jdapple/index.html},
  abstract =      {In the context of our goal to bring parallel computing into the undergraduate curriculum, we needed a parallel-programming language that was accessible to students and independent of any particular hardware platform. Finding nothing appropriate, we chose to design our own language. The result, DAPPLE, is a C++ class library designed to provide the illusion of a data-parallel programming language on conventional hardware and with conventional compilers. DAPPLE defines \emph{Vector} and \emph{Matrix} classes, with most C++ operators overloaded to provide elementwise arithmetic, and supports data-parallel operations like scans, permutations, and reductions. DAPPLE also provides a parallel if-then-else statement to restrict the scope of the above operations to partial vectors or matrices. In this article we describe the DAPPLE language, the pedagogical decisions that went into its design, and our experience using DAPPLE in the classroom. DAPPLE is freely available on the Internet.},
}

@InProceedings{kotz:dapple,
  author =        {David Kotz},
  title =         {{A DAta-Parallel Programming Library for Education (DAPPLE)}},
  booktitle =     {{Proceedings of the SIGCSE Technical Symposium on Computer Science Education}},
  year =          1995,
  month =         {March},
  pages =         {76--81},
  publisher =     {ACM},
  copyright =     {ACM},
  DOI =           {10.1145/199688.199730},
  URL =           {https://www.cs.dartmouth.edu/~kotz/research/kotz-dapple/index.html},
  abstract =      {In the context of our overall goal to bring the concepts of parallel computing into the undergraduate curriculum, we set out to find a parallel-programming language for student use. To make it accessible to students at all levels, and to be independent of any particular hardware platform, we chose to design our own language, based on a data-parallel model and on C++. The result, DAPPLE, is a C++ class library designed to provide the illusion of a data-parallel programming language on conventional hardware and with conventional compilers. DAPPLE defines \emph{Vectors} and \emph{Matrices} as basic classes, with all the usual C++ operators overloaded to provide elementwise arithmetic. In addition, DAPPLE provides typical data-parallel operations like scans, permutations, and reductions. Finally, DAPPLE provides a parallel if-then-else statement to restrict the scope of the above operations to partial vectors or matrices.},
}

@InProceedings{johnson:freshmen,
  author =        {Donald Johnson and David Kotz and Fillia Makedon},
  title =         {{Teaching Parallel Computing to Freshmen}},
  booktitle =     {{Proceedings of the Conference on Parallel Computing for Undergraduates}},
  organization =  {Colgate University},
  editor =        {Chris Nevison},
  year =          1994,
  month =         {June},
  numpages =      7,
  publisher =     {Colgate University},
  copyright =     {Colgate University},
  URL =           {https://www.cs.dartmouth.edu/~kotz/research/johnson-freshmen/index.html},
  abstract =      {Parallelism is the future of computing and computer science and should therefore be at the heart of the CS curriculum. Instead of continuing along the evolutionary path by introducing parallel computation ``top down'' (first in special junior-senior level courses), we are taking a radical approach and introducing parallelism at the earliest possible stages of instruction. Specifically, we are developing a completely new freshman-level course on data structures that integrates parallel computation naturally, and retains the emphasis on laboratory instruction. This will help to steer our curriculum as expeditiously as possible toward parallel computing. \par  Our approach is novel in three distinct and essential ways. First, we will teach parallel computing to freshmen in a course designed from beginning to end to do so. Second, we will motivate the course with examples from scientific computation. Third, we use multimedia and visualization as instructional aids. We have two primary objectives: to begin a reform of our undergraduate curriculum with an laboratory-based freshman course on parallel computation, and to produce tools and methodologies that improve student understanding of the basic principles of parallel computing.},
}

@TechReport{kotz:dapple-tr,
  author =        {David Kotz},
  title =         {{A DAta-Parallel Programming Library for Education (DAPPLE)}},
  institution =   {Dartmouth Computer Science},
  year =          1994,
  month =         {November},
  number =        {PCS-TR94-235},
  copyright =     {David Kotz},
  URL =           {https://www.cs.dartmouth.edu/~kotz/research/kotz-dapple-tr/index.html},
  abstract =      {In the context of our overall goal to bring the concepts of parallel computing into the undergraduate curriculum, we set out to find a parallel-programming language for student use. To make it accessible to students at all levels, and to be independent of any particular hardware platform, we chose to design our own language, based on a data-parallel model and on C++. The result, DAPPLE, is a C++ class library designed to provide the illusion of a data-parallel programming language on conventional hardware and with conventional compilers. DAPPLE defines \emph{Vectors} and \emph{Matrices} as basic classes, with all the usual C++ operators overloaded to provide elementwise arithmetic. In addition, DAPPLE provides typical data-parallel operations like scans, permutations, and reductions. Finally, DAPPLE provides a parallel if-then-else statement to restrict the scope of the above operations to partial vectors or matrices.},
}

@Misc{kotz:dapple-sw,
  author =        {David Kotz},
  title =         {{DAta-Parallel Programming Library for Education DAPPLE}},
  howpublished =  {a C++ class library that provides the illusion of data-parallel programming on sequential computers},
  year =          1994,
  copyright =     {the author},
  URL =           {https://www.cs.dartmouth.edu/~kotz/research/kotz-dapple-sw/index.html},
  abstract =      {DAPPLE is a C++ class library designed to provide the illusion of a data-parallel programming language on conventional hardware and with conventional compilers. DAPPLE defines Vectors and Matrices as basic classes, with all the C operators overloaded to provide for elementwise arithmetic. In addition, DAPPLE provides typical data-parallel operations such as scans, permutations, and reductions. Finally, DAPPLE provides a parallel if-then-else statement to restrict the context of the above operations to subsets of vectors or matrices.},
}