Languages and Compilers for Parallel Computing

1. Front Matter

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2. Automatic Scaling of OpenMP Beyond Shared Memory

   • Okwan Kwon, Fahed Jubair, Seung-Jai Min, Hansang Bae, Rudolf Eigenmann, Samuel P. Midkiff

   Pages 1-15

3. A Methodology for Fine-Grained Parallelism in JavaScript Applications

   • Jeffrey Fifield, Dirk Grunwald

   Pages 16-30

4. Evaluation of Power Consumption at Execution of Multiple Automatically Parallelized and Power Controlled Media Applications on the RP2 Low-Power Multicore

   • Hiroki Mikami, Shumpei Kitaki, Masayoshi Mase, Akihiro Hayashi, Mamoru Shimaoka, Keiji Kimura et al.

   Pages 31-45

5. Double Inspection for Run-Time Loop Parallelization

   • Michael Philippsen, Nikolai Tillmann, Daniel Brinkers

   Pages 46-60

6. A Hybrid Approach to Proving Memory Reference Monotonicity

   • Cosmin E. Oancea, Lawrence Rauchwerger

   Pages 61-75

7. OpenCL as a Programming Model for GPU Clusters

   • Jungwon Kim, Sangmin Seo, Jun Lee, Jeongho Nah, Gangwon Jo, Jaejin Lee

   Pages 76-90

8. CellCilk: Extending Cilk for Heterogeneous Multicore Platforms

   • Tobias Werth, Silvia Schreier, Michael Philippsen

   Pages 91-105

9. OPELL and PM: A Case Study on Porting Shared Memory Programming Models to Accelerators Architectures

   • Joseph B. Manzano, Ge Gan, Juergen Ributzka, Sunil Shrestha, Guang R. Gao

   Pages 106-123

10. Optimizing the Concurrent Execution of Locks and Transactions

    • Justin E. Gottschlich, JaeWoong Chung

    Pages 124-140

11. A Study of the Usefulness of Producer/Consumer Synchronization

    • Hao Lin, Hansang Bae, Samuel P. Midkiff, Rudolf Eigenmann, Soohong P. Kim

    Pages 141-155

12. Lock-Free Resizeable Concurrent Tries

    • Aleksandar Prokopec, Phil Bagwell, Martin Odersky

    Pages 156-170

13. Fine-Grained Treatment to Synchronizations in GPU-to-CPU Translation

    • Ziyu Guo, Xipeng Shen

    Pages 171-184

14. A Mutable Hardware Abstraction to Replace Threads

    • Sean Halle, Albert Cohen

    Pages 185-202

15. Dynamic Task Parallelism with a GPU Work-Stealing Runtime System

    • Sanjay Chatterjee, Max Grossman, Alina Sbîrlea, Vivek Sarkar

    Pages 203-217

16. A Code Merging Optimization Technique for GPU

    • Ryan Taylor, Xiaoming Li

    Pages 218-236

17. Static Compilation Analysis for Host-Accelerator Communication Optimization

    • Mehdi Amini, Fabien Coelho, François Irigoin, Ronan Keryell

    Pages 237-251

18. Scheduling Support for Communicating Parallel Tasks

    • Jörg Dümmler, Thomas Rauber, Gudula Rünger

    Pages 252-267

19. Polytasks: A Compressed Task Representation for HPC Runtimes

    • Daniel Orozco, Elkin Garcia, Robert Pavel, Rishi Khan, Guang R. Gao

    Pages 268-282

20. Detecting False Sharing in OpenMP Applications Using the DARWIN Framework

    • Besar Wicaksono, Munara Tolubaeva, Barbara Chapman

    Pages 283-297

This book constitutes the thoroughly refereed post-conference proceedings of the 24th International Workshop on Languages and Compilers for Parallel Computing, LCPC 2011, held in Fort Collins, CO, USA, in September 2011. The 19 revised full papers presented and 19 poster papers were carefully reviewed and selected from 52 submissions. The scope of the workshop spans the theoretical and practical aspects of parallel and high-performance computing, and targets parallel platforms including concurrent, multithreaded, multicore, accelerator, multiprocessor, and cluster systems.

• automatic parallelization
• cache coherence
• communication optimization
• runtime systems
• work-stealing
• data structures

• Computer Science Department, Colorado State University, Fort Collins, USA

  Sanjay Rajopadhye, Michelle Mills Strout

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