Par Lab logo   Parallel Computing Laboratory

Location: 565 Soda Hall
Time: 12:45- 4:00pm

The heart of our research agenda at the Parallel Computing Laboratory is the development of parallel software. This agenda is driven by compelling applications developed by domain experts in the many areas of expertise: applications, software engineering, programming languages, libraries, testing, operating systems, and computer architecture. We focus on exciting new applications in the areas of personal health, image retrieval, music, speech understanding, and web browsers‐ areas that need much more computing horsepower to run well, rather than on legacy programs that already run well on today's computers. The Par Lab is the result of Berkeley being the unanimous top choice by Intel and Microsoft for a $10M, 5-year Universal Parallel Computing Research Center. Samsung Electronics is our affiliate member.


1. Partitioned Convolution for Real-Time Audio Effect Processing—Eric Battenberg

2. pplication-level Trade-offs for WFST-based Large Vocabulary Continuous Speech Recognition on a Graphics Processing Unit—Jike Chong

3. SEJITS: Raising the Abstraction Level of Productivity Programming—Armando Fox

4. Band Matrix Optimization within LAPACK's xGETRF—Andrew Gearhart

5. Clinically Feasible Advanced MRI Reconstruction—Mark Murphy

6. Parallel Webpage Layout Demo—Leo Meyerovich

7. Towards Robust, Real-Time Human-Detection and Pose Estimation—Michael Anderson

8. Communication-Optimal Eigenvalue/SVD Algorithms—Grey Ballard

9. Using FPGAs to Simulate Novel Datacenter Network Architectures at Scale—David Patterson

10. PySKI: The Python Sparse Kernel Interface—Erin Carson

11. On efficient solutions for variational optical flow problems—Narayanan Sundaram

12. Parallel Option Pricing with Crank-Nicolson Method—Ekaterina Gonina

13. Re-architecting DRAM with Silicon Photonics—Scott Beamer

14. Implementing band solvers in MAGMA—Razvan Carbunescu

15. Tessellation OS: Design and Implementation Status—Kevin Klues, David Zhu, and Paul Pearce

16. Tessellation OS: Partition Management and Two-level Scheduling—Juan A. Colmenares

17. Spatial Resource Allocation on Manycore Platforms Using Predictive Performance Models—Sarah Bird, Henry Cook

18. Software Knows Best: A Case for Hardware Transparency and Measurability—Sarah Bird

19. Lithe: Composing Parallel Software Efficiently—Heidi Pan

20. Trace Simplification for Effective Debugging of Concurrent Programs—Nick Jalbert

21. Programming with Angelic Nondeterminism—Joel Galenson, Shaon Barman, Nicholas Tung

22. Copperhead: A Programming Framework for Data Parallelism—Bryan Catanzaro

23. Communication-avoiding linear algebra—Grey Ballard

24. An Efficient, High Quality Object Recognition System—Bor-Yiing Su

25. Mapping Computer Graphics Apps to a Maven Vector-Thread Core—Alex Bishara, Richard Xia

26. Computational Personal Medicine in the Multicore/Manycore Era—Ben-Salah, Carbunescu, Chaplin

27. An Effective Dynamic Analysis for Detecting Generalized Deadlocks—Pallavi Joshi

28. Productivity Language for Sparse Matrices—Gilad Arnold

29. Maven: A data parallel architecture for par lab". Yunsup Lee,Rimas,Chris Celio.