© Vipin Kumar IPDPS-2011, May 18, 2011 1

25th Year Panel – WHAT’S AHEAD

Vipin Kumar

University of Minnesota

kumar@cs.umn.edu http://www.cs.umn.edu/~kumar

© Vipin Kumar IPDPS-2011, May 18, 2011 2

Applications

What will be the next wave of grand challenge problems to focus on in the next 10 years and beyond ?

© Vipin Kumar IPDPS-2011, May 18, 2011 3

Compute centric to Data Centric

Compute Intensive

Data Intensive

Transition:

© Vipin Kumar IPDPS-2011, May 18, 2011 4

Compute centric to Data Centric

Compute Intensive

Data Intensive

Transition:

Enabled by 6 decades of exponential growth in computing power, storage capacity, networking and more recent development of the Internet technology, data and compute clouds

© Vipin Kumar IPDPS-2011, May 18, 2011 5

Compute centric to Data Centric

Compute Intensive

Data Intensive

Transition:

© Vipin Kumar IPDPS-2011, May 18, 2011 6

Great Challenges Facing the Society

Improving health care and reducing costs

Finding alternative/ green energy sources

Predicting the impact of climate change

Reducing hunger and poverty by increasing agriculture production

© Vipin Kumar IPDPS-2011, May 18, 2011 7

Scalable Data Analysis

General Circulation Models: Mathematical models with physical equations based on fluid dynamics

Figure Courtesy: ORNL

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Parameterization and non-linearity of differential equations are sources for uncertainty!

Cell

Clouds

LandOcean

Example: Understanding Climate Change

Detection of Global Dipole Structure

© Vipin Kumar IPDPS-2011, May 18, 2011 8

Most challenging algorithmic problems

Dense vs. Sparse

Structured versus Unstructured

Static vs. Dynamic

Data intensive computations tend to be unstructured, sparse and dynamic

Restructuring algorithms for locality key to scalability Crucial in the context of emerging architectures based on multi-core,

GPUs,…

© Vipin Kumar IPDPS-2011, May 18, 2011 9

Software

How will we ever be able to hide parallelism obstacles for the masses and what is the road forward towards that ?

© Vipin Kumar IPDPS-2011, May 18, 2011 10

Computing Platforms

How will we be able to keep improving the performance growth of the past and what will be the major challenges in the next 10 years and beyond that ? What technical barriers are anticipated and what disruptive technologies are behind the corner ?

© Vipin Kumar IPDPS-2011, May 18, 2011 11

Do We Need Benchmarks Specific to Data Intensive

Computing ?

Performance metrics of several benchmarks gathered from Vtune• Cache miss ratios, Bus usage, Page faults etc.

Benchmark applications were grouped using Kohenen clustering to spot trends:

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Reference: [Pisharath J., Zambreno J., Ozisikyilmaz B., Choudhary A., 2006]