Recent & Highlighted Items

Wen-mei Hwu Named Recipient of 2014 IEEE Computer Society B. Ramakrishna Rau Award

University of Illinois at Urbana-Champaign Professor Wen-mei W. Hwu has been named the 2014 recipient of the IEEE Computer Society B. Ramakrishna Rau Award for his work in Instruction-Level Parallelism.

The Rau Award recognizes significant accomplishments in the field of microarchitecture and compiler code generation. Hwu was recognized “for contributions to Instruction Level Parallelism technology, including compiler optimization, program representation, microarchitecture, and applications.”
 
The award, which comes with a $2,000 honorarium and a certificate, will be given out on Tuesday, 16 December at the ACM/IEEE International Symposium on Microarchitecture (MICRO) in Cambridge, UK. IEEE Computer Society established the award in 2010 in memory of the late Bob Rau, an HP Senior Fellow.
 

Columbia University - Invited Talk: Moving Towards Exascale with Lessons Learned from GPU Computing (October 14, 2014)

The rise of GPU computing has significantly boosted the pace of progress in numeric methods, algorithm design, and programming techniques for developing scalable applications. Much has been learned about of algorithms, languages, compilers and hardware architecture in this movement. I will discuss some insights gained and a vision for moving applications into exascale computing.

University of British Columbia: Invited Distinguish Lecture (October 5, 2014)

The rise of GPU computing has significantly boosted the pace of progress in numeric methods, algorithm design, and programming techniques for developing scalable applications. Much has been learned about of algorithms, languages, compilers and hardware architecture in this movement. I will discuss some insights gained and a vision for moving applications into exascale computing.

Christopher Rodrigues Doctoral Dissertation: Supporting High-Level, High-Performance Parallel Programming with Library-Driven Optimization

This dissertation presents Triolet, a programming language and compiler for high-level programming of parallel loops for high-performance execution on clusters of multicore computers. Triolet’s design demonstrates that it is possible to decouple the design of a compiler from the implementation of parallelism without sacrificing performance or ease of use. This programming approach opens the potential for future research into parallel programming frameworks.

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Recent & Highlighted Papers

2014

"Adaptive Cache Management for Energy-efficient GPU Computing", Chen, Xuhao; Chang, Li-Wen; Rodrigues, Christopher I.; Lv, Jie; Wang, Zhiying; Hwu, Wen-mei, Proceedings of the 47th Annual IEEE/ACM International Symposium on Microarchitecture, December 2014 . [more...]
 
"Supporting High-Level, High-Performance Parallel Programming with Library-Driven Optimization", Rodrigues, Christopher I., University of Illinois Doctoral Disertation, May 2014. [more...]
 
"Automatic execution of single-GPU computations across multiple GPUs", Cabezas, Javier; Vilanova, Lluis; Gelado, Isaac; Jablin, Tom; Navarro, Nacho; Hwu, Wen-mei, Proceedings of the 23rd international conference on Parallel architectures and compilation (PACT '14). [more...]
 
"High Performance Histogramming on Massively Parallel Processors", Ross, Greg, University of Illinois Masters Disertation, August 2014. [more...]
 
"Scalable Parallel Tridiagonal Algorithms with Diagonal Pivoting and Their Optimization for Many-core Architectures", Chang, Li-Wen, University of Illinois Master Thesis, July 2014? . [more...]
 
"Dynamic Loop Vectorization for Executing OpenCL Kernels on CPUs", El Hajj, Izzat, University of Illinois Masters Disertation, May 2014. [more...]