Proceedings of GPGPU
All papers [zip]
9:30 – 10:20 Session 1: Applications I
- High Performance Predictable Histogramming on GPUs: Exploring and Evaluating Algorithm Tradeoffs,
Cedric Nugteren, Gert–Jan van den Braak, Henk Corporaal and Bart Mesman (Eindhoven University of Tecnology,
Netherlands).[pdf]
- Automatically Generating and Tuning GPU Code for
Sparse Matrix Vector Multiplication from a High–Level Representation,
Dominik Grewe (University of Edinburgh) and Anton Lokhmotov (ARM). [pdf]
10:45 – 12:00 Session 2: Optimizations
- Reducing Branch Divergence in GPU Programs,
Tianyi David Han and Tarek Abdelrahman (Univ. of Toronto).[pdf]
- Register Packing for Cyclic Reduction: A Case Study,
Andrew Davidson and John Owens (University of California at Davis).[pdf]
- Caracal: Dynamic Translation of Runtime Environments for GPUs,
Rodrigo Dominguez, Dana Schaa and David Kaeli (Northeastern University).[pdf]
1:30 – 2:45 Session 3: Applications II
- Fast Mersenne Prime Testing on the GPU.
Andrew Thall (Alma College). [pdf]
- Floating–Point Data Compression at 75 Gb/s on a GPU,
Molly ONeil and Martin Burtscher, (Texas State – San Marcos).[pdf]
- Real time Rendering and Dynamic Updating of 3D Volumetric Data
Andrew Miller, Vishal Jain and Joseph Mundy, (Computer Vision Group).[pdf]
3:15 – 4:30 Session 4: Instrumentation and Analysis
- A Framework for Dynamically Instrumenting GPU Compute Applications within GPU Ocelot,
Naila Farooqui,Andrew Kerr, Gregory Diamos, Sudhakar Yalamanchili and
Karsten Schwan (Georgia Tech).[pdf]
- Analyzing Program Flow within a Many Kernel OpenCL Application,
Perhaad Mistry (Northeastern Univ.), Chris Gregg (Univ. of Virginia), Norman Rubin (AMD),
David Kaeli (Northeastern University) and Kim Hazelwood (Univ. of Virginia). [pdf]
- Quantifying NUMA and Contention Effects in Multi–GPU Systems
Kyle Spafford (Oak Ridge National Labs), Jeremy Meredith (Oak Ridge National Labs)
and Jeffrey Vetter (Oak Ridge National Labs and Georgia Tech). [pdf]
5:10 – 6:00 Session 5: Applications III
- A New Method for GPU based Irregular Reductions and Its Application to K–Means Clustering,
Balaji Dhanasekaran (University of Virginia) and Norman Rubin (AMD).[pdf]
- Unstructured Grid Applications on GPU, Performance Analysis and Improvement,
Lizandro Solano–Quinde(Iowa State Univ.), Brett Bode (NCSA), Z.J. Wang ( Iowa State Univ.)
and Arun Somani (Iowa State Univ.). [pdf]