2nd Workshop on Performance Engineering and Applications (WPEA)

The workshop on performance engineering and applications (WPEA) aims at providing a platform for scientific researchers and practitioners to discuss performance engineering for real-world problems in parallel and distributed environments such as cluster, grid, peer-to peer network, GP-GPU, multi-core systems and clouds. The workshop offers an opportunity to discuss systems, architectures, tools, and optimization algorithms that are parallel in nature and hence make use of advancements in high performance computing. The workshop also offers an opportunity to discuss advanced methodologies, tools, techniques and algorithms to enhance performance for emerging applications. The applications intended for discussions are, but not limited to, bio-informatics, earth and climate sciences, physical sciences and engineering, telecommunication, finance etc. Various algorithms and optimization techniques that tend to bridge the gap between peak performance and sustained performance for various applications will be discussed.

Topics

We seek submissions on broad topics which include, but not limited to:
  • Performance Engineering - standard practices and emerging trends
  • Systems and tools for architecture, code, and platform optimization in performance engineering.
  • System software, tools, techniques, algorithms and methodologies for performance engineering.
  • Algorithms for performance engineering Automation of optimization techniques, machine learning for optimization.
  • Workload characterization and emerging applications: bio-informatics, finance, molecular dynamics, fluid dynamics, telecommunication, weather modeling, astrophysics, clinical, scripting languages, runtime environment, big data, data analytics etc.

Important Dates

  • August 6 - Paper Submission deadline
  • September 4 - Author Notification
  • September 10 - Camera ready paper deadline
  • December 18 - Workshop date

Submissions

Submissions describing original, unpublished recent results related to the workshop theme, upto 6 pages in IEEE conference format can be submitted through the easychair conference system, following this link:https://www.easychair.org/conferences/?conf=wpea13

The submissions must be in pdf format.

While the preferred mode of submission is through the easychair conference system, authors may also submit their manuscripts over email to pradeep.rao@in.ibm.com or dhchahal@in.ibm.com.

Please note that HiPC has mandated that atleast one of the authors of the selected workshop paper (preferably the presenting author) should REGISTER before submitting the CAMERA READY version of their paper.

Workshop Schedule

14:00 - 14:40 
Data-Parallel Implementation of Quadrature Methods for Complex Numbers
Sandeep Koranne, Mentor Graphics Corporation, USA
14:40 - 15:20 
A Novel Technique to Improve Parallel Program Performance Co-executing with Dynamic Workloads
Murali Krishna Emani and Michael O'Boyle, University of Edinburgh, UK
15:20 - 16:00 
Performance trends of multicore system for throughput computing in medical application
Madhurima Pore, Ayan Banerjee, Sandeep Gupta and Hari Tadepalli, Arizona State University and Intel
16:30 - 17:10 
Block Dimension Selection for GPU Kernels using Artificial Neural Networks
Arka Ghosh and S. Balasubramanian, Sri Sathya Sai Institute of Higher Learning, India
17:10 - 17:45 
Panel Discussion

Program Co-Chairs

  • Pradeep Rao, IBM, India

  • Dheeraj Chahal, TCS Innovations Lab, India

Technical Program Committee

Steven J Stuart, Clemson University
Erven Rohou, INRIA
Dibyendu Das, AMD
Anand Haridass, IBM
Vikram Narayana, George Washington University
P Joseph, Freescale
Sandya Mannarswamy, HP
Suparna Bhattacharya, IBM
S Balakrishnan, NVIDIA
Anasua Bhowmik, AMD
Subhasis Banerjee, IIIT-D
Madhavi Valluri, IBM
Vikram Goyal, IIIT-D

Acknowledgements

The organizers and program chairs wish to thank and acknowledge the contributions of the following reviewers who helped with their technical expertise.

  • Dharmesh Parikh, IBM
  • Chiranjib Sur, Shell
  • Saumil Merchant, IBM
  • Rajesh Tyagi , MVN