LCPC 1994: Ithaca, NY, USA

Starting Small: Fine-Grain Parallelism

• Paul Feautrier:
  Fine-Grain Scheduling under Resource Constraints. 1-15
  
• Steven Novack, Alexandru Nicolau:
  Mutation Scheduling: A Unified Approach to Compiling for Fine-Grain Parallelism. 16-30
  
• Henry G. Dietz, William E. Cohen, T. Muhammad, Timothy Mattox:
  Compiler Techniques for Fine-Grain Execution on Workstation Clusters Using PAPERS. 31-45
  

Getting Your Ducks in a Row: Alignment and Distribution

• David Bau, Induprakas Kodukula, Vladimir Kotlyar, Keshav Pingali, Paul Stodghill:
  Solving Alignment Using Elementary Linear Algebra. 46-60
  
• Eduard Ayguadé, Jordi Garcia, Mercè Gironés, Jesús Labarta, Jordi Torres, Mateo Valero:
  Detecting and Using Affinity in an Automatic Data Distribution Tool. 61-75
  
• Siddhartha Chatterjee, Robert Schreiber, Thomas J. Sheffler, John R. Gilbert:
  Array Distribution in Data-Parallel Programs. 76-91
  

Postlinear Loop Transformations

• Amy W. Lim, Monica S. Lam:
  Communication-Free Parallelization via Affine Transformations. 92-106
  
• Wayne Kelly, William Pugh:
  Finding Legal Reordering Transformations Using Mappings. 107-124
  
• William F. Appelbe, Srinivas Doddapaneni, Charles Hardnett:
  A New Algorithm for Global Optimization for Parallelism and Locality. 125-140
  

What Next?

• William Blume, Rudolf Eigenmann, Keith Faigin, John Grout, Jay Hoeflinger, David A. Padua, Paul Petersen, William M. Pottenger, Lawrence Rauchwerger, Peng Tu, Stephen Weatherford:
  Polaris: Improving the Effectiveness of Parallelizing Compilers. 141-154
  
• J. A. Trescher, Leo C. Breebaart, P. F. G. Dechering, A. B. Poelman, J. P. M. de Vreught, Henk J. Sips:
  A Formal Approach to the Compilation of Data-Parallel Languages. 155-169
  
• Tsuneo Nakanishi, Kazuki Joe, Akira Fukuda, Keijiro Araki, Hideki Saito, Constantine D. Polychronopoulos:
  The Data Partitioning Graph: Extending Data and Control Dependencies for Data Partitioning. 170-185
  

Back to Basics: Program Analysis

• Eric Stoltz, Michael Wolfe:
  Detecting Value-Based Scalar Dependence. 186-200
  
• Yi-Qing Yang, Corinne Ancourt, François Irigoin:
  Minimal Data Dependence Abstractions for Loop Transformations. 201-216
  
• Vincent Sgro, Barbara G. Ryder:
  Differences in Algorithmic Parallelism in Control Flow and Call Multigraphs. 217-233
  
• Michael G. Burke, Paul R. Carini, Jong-Deok Choi, Michael Hind:
  Flow-Insensitive Interprocedural Alias Analysis in the Presence of Pointers. 234-250
  

How to Communicate Better

• S. D. Kaushik, Chua-Huang Huang, P. Sadayappan:
  Incremental Generation of Index Sets for Array Statement Execution on Distributed-Memory Machines. 251-265
  
• Manish Gupta, Edith Schonberg, Harini Srinivasan:
  A Unified Data-Flow Framework for Optimizing Communication. 266-282
  
• Gagan Agrawal, Joel H. Saltz:
  Interprocedural Communication Optimizations for Distributed Memory Compilation. 283-299
  

Automatic Parallelization Considered Unnecessary

• J. Ramanujam, A. Mathew:
  Analysis of Event Synchronization in Parallel Programs. 300-315
  
• Jeanne Ferrante:
  Computing Communication Sets for Control Parallel Programs. 316-330
  
• Arvind Krishnamurthy, Katherine A. Yelick:
  Optimizing Parallel SPMD Programs. 331-345
  

Languages for Parallelism: Something Borrow, Something New

• Piyush Mehrotra, Matthew Haines:
  An Overview of the Opus Language and Runtime System. 346-360
  
• Calvin Lin, Lawrence Snyder:
  SIMPLE Performance Results in ZPL. 361-375
  
• Rishiyur S. Nikhil:
  Cid: A Parallel, "Shared-Memory" C for Distributed-Memory Machines. 376-390
  
• Thomas Derby, Robert B. Schnabel, Benjamin G. Zorn:
  EQ: Overview of a New Language Approach for Prototyping Scientific Computation. 391-405
  

And Now, for Something Completely Different

• Aart J. C. Bik, Peter M. W. Knijnenburg, Harry A. G. Wijshoff:
  Reshaping Access Patterns for Generating Sparse Codes. 406-420
  
• François Bodin, Elana D. Granston, Thierry Montaut:
  Evaluating Two Loop Transformations for Reducing Multiple Writer False Sharing. 421-439
  
• Jon A. Solworth, Bryan Reagan:
  Parallelizing Tree Algorithms: Overhead vs. Parallelism. 440-454
  

When Your Program Runs (Finally)

• José E. Moreira, Constantine D. Polychronopoulos:
  Autoscheduling in a Distributed Shared-Memory Environment. 455-471
  
• Krishna Kunchithapadam, Barton P. Miller:
  Optimizing Array Distributions in Data-Parallel Programs. 472-486
  
• Satoshi Sekiguchi, Kei Hiraki:
  Automatic Reduction Tree Generation for Fine-Grain Parallel Architectures when Iteration Count is Unknown. 487-496
  

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