ICS 1997: Vienna, Austria

ILP and Wide-Busses

• Jaime H. Moreno, Mayan Moudgill:
  Scalable Instruction-Level Parallelism Through Tree-Instructions. 1-11
  
• David López, Mateo Valero, Josep Llosa, Eduard Ayguadé:
  Increasing Memory Bandwidth with Wide Buses: Compiler, Hardware and Performance Trade-Offs. 12-19
  

Collective I/O

• Rajesh Bordawekar:
  Implementation of Collective I/O in the Intel Paragon Parallel File System: Initial Experiences. 20-27
  
• Ying Chen, Jarek Nieplocha, Ian T. Foster, Marianne Winslett:
  Optimizing Collective I/O Performance on Parallel Computers: A Multisystem Study. 28-35
  

Applications

• Graham D. Riley, J. Mark Bull, John R. Gurd:
  Performance Improvement through Overhead Analysis: A Case Study in Molecular Dynamics. 36-43
  
• Hyuk-Jae Lee, James P. Robertson, José A. B. Fortes:
  Generalized Cannon's Algorithm for Parallel Matrix Multiplication. 44-51
  
• Xian-He Sun, Yu Zhuang:
  A Highly Accurate Fast Solver for Helmholtz Equations. 52-59
  

Caches

• Toni Juan, Juan J. Navarro, Olivier Temam:
  Data Caches for Superscalar Processors. 60-67
  
• James Dundas, Trevor N. Mudge:
  Improving Data Cache Performance by Pre-Executing Instructions Under a Cache Miss. 68-75
  
• Antonio González, Mateo Valero, Nigel P. Topham, Joan-Manuel Parcerisa:
  Eliminating Cache Conflict Misses through XOR-Based Placement Functions. 76-83
  

Scheduling and Processor Assignment

• Kevin Hao Liu:
  Performance Study on Optimal Processor Assignment in Parallel Relational Databases. 84-91
  
• Daniel Andresen, Tao Yang:
  Multiprocessor Scheduling with Client Resources to Improve the Response Time of WWW Applications. 92-99
  

Parallel Architectures

• Mangesh Kasbekar, Shailabh Nagar, Anand Sivasubramaniam:
  pSNOW: A Tool to Evaluate Architectural Issues for NOW Environments. 100-107
  
• Taisuke Boku, Ken'ichi Itakura, Hiroshi Nakamura, Kisaburo Nakazawa:
  CP-PACS: A Massively Parallel Processor for Large Scale Scientific Calculations. 108-115
  

Object-Oriented Programming

• Naohito Sato, Satoshi Matsuoka, Jean-Marc Jézéquel, Akinori Yonezawa:
  A Methodology for Specifying Data Distribution Using Only Standard Object-Oriented Features. 116-123
  
• Elizabeth Johnson, Dennis Gannon:
  HPC++: Experiments with the Parallel Standard Template Library. 124-131
  

Routing

• Wu-chang Feng, Kang G. Shin:
  Impact of Selection Functions on Routing Algorithm Performance in Multicomputer Networks. 132-139
  
• Aniruddha S. Vaidya, Anand Sivasubramaniam, Chita R. Das:
  Performance Benefits of Virtual Channels and Adaptive Routing: An Application-Driven Study. 140-147
  

Synchronization

• Nian-Feng Tzeng, Angkul Kongmunvattana:
  Distributed Shared Memory Systems with Improved Barrier Synchronization and Data Transfer. 148-155
  
• Elena Stöhr, Michael F. P. O'Boyle:
  A Graph Based Approach to Barrier Synchronisation Minimisation. 156-163
  
• Arjan J. C. van Gemund:
  The Importance of Synchronization Structure in Parallel Program Optimization. 164-171
  

Performance

• John G. Holm, John A. Chandy, Steven Parkes, Sumit Roy, Venkatram Krishnaswamy, Gagan Hasteer, Prithviraj Banerjee:
  Performance Evaluation of Message-Driven Parallel VLSI CAD Applications on General Purpose Multiprocessors. 172-179
  
• Robert van Engelen, Ilja Heitlager, Lex Wolters, Gerard Cats:
  Incorporating Application Dependent Information in an Automatic Code Generating Environment. 180-187
  
• Vladimir Kotlyar, Keshav Pingali:
  Sparse Code Generation for Imperfectly Nested Loops with Dependences. 188-195
  

Prefetching

• José González, Antonio González:
  Speculative Execution via Address Prediction and Data Prefetching. 196-203
  
• Ando Ki, Alan E. Knowles:
  Adaptive Data Prefetching Using Cache Information. 204-212
  

Communication and Multicasts

• Jörg Cordsen, Hans Werner Pohl, Wolfgang Schröder-Preikschat:
  Performance considerations in software multicasts. 213-220
  
• William Pugh, Evan Rosser:
  Iteration Space Slicing and Its Application to Communication Optimization. 221-228
  

Tree-based and Semi-Structured Applications

• Nikos Chrisochoides, Induprakas Kodukula, Keshav Pingali:
  Compiler and Run-Time Support for Semi-Structured Applications. 229-236
  
• Maria Cristina Pinotti, Sajal K. Das, Falguni Sarkar:
  Conflict-Free Template Access in k-ary and Binomial Trees. 237-244
  

Distributed Shared Memory

• Daniel J. Scales, Kourosh Gharachorloo:
  Design and Performance of the Shasta Distributed Shared Memory Protocol. 245-252
  
• Hironori Nakajo, Satoshi Ohtani, Takashi Matsumoto, Masadi Kohata, Kei Hiraki, Yukio Kaneda:
  An I/O Network Architecture of the Distributed Shared-Memory Massively Parallel Computer JUMP-1. 253-260
  

Compilers

• Thomas Fahringer, Bernhard Scholz:
  Symbolic Evaluation for Parallelizing Compilers. 261-268
  
• Mahmut T. Kandemir, J. Ramanujam, Alok N. Choudhary:
  A Compiler Algorithm for Optimizing Locality in Loop Nests. 269-276
  
• Rizos Sakellariou, John R. Gurd:
  Compile-Time Minimisation of Load Imbalance in Loop Nests. 277-284
  

Hardware Features for Performance

• Shlomo Reches, Shlomo Weiss:
  Implementation and Analysis of Path History in Dynamic Branch Prediction Schemes. 285-292
  
• Roger Espasa, Mateo Valero:
  A Victim Cache for Vector Registers. 293-300
  
• Soo-Mook Moon, Kemal Ebcioglu:
  Performance Analysis of Tree VLIW Architecture for Exploiting Branch ILP in Non-Numerical Code. 301-308
  

Data Placement and Transformation

• Michael F. P. O'Boyle, Peter M. W. Knijnenburg:
  Non-Singular Data Transformations: Definition, Validity and Applications. 309-316
  
• Somnath Ghosh, Margaret Martonosi, Sharad Malik:
  Cache Miss Equations: An Analytical Representation of Cache Misses. 317-324
  
• Jai-Hoon Kim, Nitin H. Vaidya:
  Adaptive Migratory Scheme for Distributed Shared Memory. 325-332
  

Performance Prediction and Coding

• Dieter F. Kvasnicka, Christoph W. Ueberhuber:
  Developing Architecture Adaptive Algorithms Using Simulation with MISS-PVM for Performance Prediction. 333-339
  
• Jeff Bilmes, Krste Asanovic, Chee-Whye Chin, James Demmel:
  Optimizing Matrix Multiply Using PHiPAC: A Portable, High-Performance, ANSI C Coding Methodology. 340-347
  

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