hpc trends for 2013

HPC Trends for 2013

Addison Snell addison@intersect360.com

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Topics for Discussion •  Shifts in budget allocations •  Processor architectures and their implications

–  Memory –  Programming models –  Efficiency

•  Big Data and its potential for HPC •  What’s cloud got to do with it

HPC Budget Distribution by Year • ~$29B total market implies

~$44B total budget • Hardware declined every

year until sudden rebound in 2012

• Facilities increased every year until reversing in 2012

• Public cloud is a small part of the market

From HPC User Site Census The primary challenges for users are: •  How to plan the balance between processors per node,

cores per processor, memory per node, I/O and interconnect on node, total nodes, etc.

•  How to adapt applications for node parallelism and on-chip (i.e., multi-core) parallelism.

•  How to organize the overall job mix. Smaller nodes may be a better fit for processing large numbers of small jobs or large set of jobs with a broad range of requirements. Larger nodes may work best with a job mix skewed to larger problems.

Memory Configuration

Accelerators (Mostly NVIDIA GPUs)

Challenges of Architecture Trends •  Power consumption •  Cost of memory •  New models of parallelization •  Languages and programming models, especially

for accelerated solutions •  System efficiency •  Personnel for administration, optimization,

programming services, etc.

Technical vs. Enterprise Computing

Technical Computing •  Top-line missions:

–  Find the oil –  Design the minivan –  Cure the disease

•  Driven by price/performance

•  Fast adoption of new technologies, algorithms, and approaches

Enterprise Computing •  Keeps business running

–  Communicate/collaborate –  Market and sell the product –  Accounting, HR, finance, …

•  Driven by RAS: reliability, availability, serviceability

•  Slow adoption of new technologies, algorithms, and approaches

Where Big Data Comes From •  “Big Data” is not a specific application type, but

rather a trend – or even a collection of trends – spanning multiple application types

•  Data growing in multiple ways: –  More data (volume of data) –  More types of data (variety of data) –  Faster ingest of data (velocity of data) –  Accessibility of data (internet, instrumentation, …)

•  Exceeds organizational ability to manage data or make competitive decisions based on it

Different Types of Big Data •  “Big” in Big Data is a relative term, like “High” in

High Performance Computing, not absolute TB or IOPS

•  Different types of challenges: –  Large files –  Large numbers of files –  Many users of files (concurrent access, copies) –  Fast rate of ingest –  Long or short lifespan of data

•  Implication: If data, then value.

Scaling an Enterprise Data Infrastructure

Parallel file systems

I/O interconnects

Operating systems

Cloud

Important Insights on Big Data 1.  It is much broader than Hadoop – many

different types of users and applications. 2.  Money is being spent on it now – often 25% of

the annual IT budget. 3.  Performance matters – even enterprise users

are buying based on performance.

Big Data trends will lead to the adoption of HPC technologies in more areas.

A Digression on Public HPC Clouds

•  Cost Models •  Barriers

Percent Rating Cloud Barrier “Significant”

Data movement and security are “top” barriers,

but there is a long list

•  From special study on HPC and cloud, 2011

•  N = 139 – 144

Cloud + Big Data: When Trends Collide

•  Cloud is a major business computing trend. Big Data is a major business computing trend. Therefore …

•  But the barriers to Big Data in cloud are the same as HPC in cloud (security, data movement, etc.)

•  Not as simple as offloading everything to Amazon •  If cloud is a priority, invest in management software to

coordinate workloads across public and private

I like sushi. I like ice cream. Therefore I like sushi-flavored ice cream.

Conclusions for HPC in 2013 •  Users have options for breakout performance,

but they all require effort –  Users are evaluating multi-core, accelerators, cloud,

programming models, etc., but not committing yet. –  What solutions will be efficient? –  What are the software and human skills required?

•  There is an opportunity to expand the use of HPC technology

•  Big Data is a bigger near-term opportunity than “Missing Middle” for most technologies

HPC Trends for 2013

Addison Snell addison@intersect360.com