Languages and Compilers for Parallel Computing

1. Front Matter

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2. CUDA-Lite: Reducing GPU Programming Complexity

   • Sain-Zee Ueng, Melvin Lathara, Sara S. Baghsorkhi, Wen-mei W. Hwu

   Pages 1-15

3. MCUDA: An Efficient Implementation of CUDA Kernels for Multi-core CPUs

   • John A. Stratton, Sam S. Stone, Wen-mei W. Hwu

   Pages 16-30

4. Automatic Pre-Fetch and Modulo Scheduling Transformations for the Cell BE Architecture

   • Nikola Vujić, Marc Gonzàlez, Xavier Martorell, Eduard Ayguadé

   Pages 31-46

5. Efficient Set Sharing Using ZBDDs

   • Mario Méndez-Lojo, Ondřej Lhoták, Manuel V. Hermenegildo

   Pages 47-63

6. Register Bank Assignment for Spatially Partitioned Processors

   • Behnam Robatmili, Katherine Coons, Doug Burger, Kathryn S. McKinley

   Pages 64-79

7. Smashing: Folding Space to Tile through Time

   • Nissa Osheim, Michelle Mills Strout, Dave Rostron, Sanjay Rajopadhye

   Pages 80-93

8. Identification of Heap–Carried Data Dependence Via Explicit Store Heap Models

   • Mark Marron, Darko Stefanovic, Deepak Kapur, Manuel Hermenegildo

   Pages 94-108

9. On the Scalability of an Automatically Parallelized Irregular Application

   • Martin Burtscher, Milind Kulkarni, Dimitrios Prountzos, Keshav Pingali

   Pages 109-123

10. Statistically Analyzing Execution Variance for Soft Real-Time Applications

    • Tushar Kumar, Romain Cledat, Jaswanth Sreeram, Santosh Pande

    Pages 124-140

11. Minimum Lock Assignment: A Method for Exploiting Concurrency among Critical Sections

    • Yuan Zhang, Vugranam C. Sreedhar, Weirong Zhu, Vivek Sarkar, Guang R. Gao

    Pages 141-155

12. Set-Congruence Dynamic Analysis for Thread-Level Speculation (TLS)

    • Cosmin E. Oancea, Alan Mycroft

    Pages 156-171

13. Thread Safety through Partitions and Effect Agreements

    • Nicholas D. Matsakis, Thomas R. Gross

    Pages 172-186

14. P-Ray: A Software Suite for Multi-core Architecture Characterization

    • Alexandre X. Duchateau, Albert Sidelnik, María Jesús Garzarán, David Padua

    Pages 187-201

15. Scalable Implementation of Efficient Locality Approximation

    • Xipeng Shen, Jonathan Shaw

    Pages 202-216

16. P-OPT: Program-Directed Optimal Cache Management

    • Xiaoming Gu, Tongxin Bai, Yaoqing Gao, Chengliang Zhang, Roch Archambault, Chen Ding

    Pages 217-231

17. Compiler-Driven Dependence Profiling to Guide Program Parallelization

    • Peng Wu, Arun Kejariwal, Călin Caşcaval

    Pages 232-248

18. gluepy: A Simple Distributed Python Programming Framework for Complex Grid Environments

    • Ken Hironaka, Hideo Saito, Kei Takahashi, Kenjiro Taura

    Pages 249-263

19. A Fully Parallel LISP2 Compactor with Preservation of the Sliding Properties

    • Xiao-Feng Li, Ligang Wang, Chen Yang

    Pages 264-278

20. A Case Study in Tightly Coupled Multi-paradigm Parallel Programming

    • Sayantan Chakravorty, Aaron Becker, Terry Wilmarth, Laxmikant Kalé

    Pages 279-291

In 2008 the Workshop on Languages and Compilers for Parallel Computing left the USA to celebrate its 21st anninversary in Edmonton, Alberta, Canada. Following its long-established tradition, the workshop focused on topics at the frontierofresearchanddevelopmentinlanguages,optimizingcompilers,appli- tions, and programming models for high-performance computing. While LCPC continues to focus on parallel computing, the 2008 edition included the pres- tation of papers on program analysis that are precursors of high performance in parallel environments. LCPC 2008 received 35 paper submissions. Eachpaper received at least three independent reviews, and then the papers and the referee comments were d- cussed during a Program Committee meeting. The PC decided to accept 18 papers as regular papers and 6 papers as short papers. The short papers appear at the end of this volume. The LCPC 2008 program was fortunate to include two keynote talks. Keshav Pingali’s talk titled “Amorphous Data Parallelism in Irregular Programs” - gued that irregular programs have data parallelism in the iterative processing of worklists. Pingali described the Galois system developed at The University of Texas at Austin to exploit this kind of amorphous data parallelism. The second keynote talk, “Generic ParallelAlgorithms in Threading Building Bocks (TBB),” presented by Arch Robison from Intel Corporation addressed very practical aspects of using TBB, a production C++ library, for generic p- allel programming and contrasted TBB with the Standard Template Library (STL).

• LISP
• Python
• Scheduling
• algorithms
• class analysis
• compilers
• complexity
• concurrency
• context sensitivity
• distributed memory systems
• distributed systems
• dynamic parallelization
• garbage collection
• high performance computing
• integer linear programming
• data structures

• Department of Computing Science, University of Alberta, Edmonton, Canada

  José Nelson Amaral

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