For the full video of this presentation, please visit: http://www.embedded-vision.com/platinum-members/bdti/embedded-vision-training/videos/pages/may-2014-embedded-vision-summit-techni-0 For more information about embedded vision, please visit: http://www.embedded-vision.com Jeff Bier, President and co-founder of BDTI and founder of the Embedded Vision Alliance, presents the "Trends and Recent Developments in Processors for Vision" tutorial at the May 2014 Embedded Vision Summit. Processor suppliers are investing intensively in new processors for vision applications, employing a diverse range of architecture approaches to meet the conflicting requirements of high performance, low cost, energy efficiency, and ease of application development. In this presentation, Bier draws from BDTI's ongoing processor evaluation work to highlight significant recent developments in processors for vision applications, including mobile application processors, graphics processing units, and specialized vision processors. He also explores what BDTI considers to be the most significant trends in processors for vision—such as the increasing use of heterogeneous architectures—and the implications of these trends for system designers and application developers.

1. Copyright © 2014 BDTI 1
Jeff Bier, President, BDTI
May 29, 2014
Trends and Recent Developments in
Processors for Vision

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• BDTI provides:
• Product development engineering services
• Emphasis on optimization for performance, cost and power
• Benchmarking and evaluation
• For technology selection, feasibility studies, competitive
analysis and proof points
• Focused on:
• Algorithm-intensive applications: vision, video, audio, wireless
• Embedded processors, tools and techniques
“BDTI’s deliverables were orders of magnitude better than other
vendors’. BDTI has set a new standard for quality.”
– Group Program Manager, Fortune 500 Systems & Software Co.
See our fun vision demos in the Technology Showcase!
About BDTI

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The Fundamental Challenge
High Performance
Low Cost
Low Power
Small
Ease of
Development
(and Optimization)
Flexibility

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Processing Efficiency vs. Development Effort
Performance/$
Performance/W
Development
Effort

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Reality
Performance/$
Performance/W
Development
Effort

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A Rising Tide
Performance/$
Performance/W
Development
Effort

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Trend: Heterogeneous Architectures
Performance/$
Performance/W
Development
Effort

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• Very heterogeneous processors
• Benefit from huge investments by suppliers, because mobile market is
huge
• Hardware performance, efficiency, integration
• Application development infrastructure
• Mobile apps have become a primary locus of software development
• APs can be difficult to buy and use for embedded applications
• APs are used in some embedded applications (sometimes in mobile
device form, sometimes via a system-on-module)
Trend: Mobile Application Processors
CPU GPU
DSP
ISP
VPU

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• Graphics processing units (GPUs) are massively parallel machines
• Over the past decade, GPUs and their tools have evolved to support
non-graphics workloads (“general-purpose GPU” or “GPGPU”)
• Widely used in demanding workstation and data center applications
in which data parallelism is abundant
• E.g., Photoshop, FFTs
• NVIDIA pioneered this concept with CUDA
• Others have joined via OpenCL and RenderScript
• Important recent developments:
• Now in mobile application processors and embedded processors
• Expanding support via libraries, code examples,
optimized middleware
• OpenCL support
• HSA (Heterogeneous System Architecture)
Trend: General-Purpose GPU

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• As more vision applications achieve high volumes, vision-specific
processors are emerging
• All are co-processors, working in tandem with a CPU
• Many are sold as licensable IP for custom chips:
• CogniVue, CEVA, Cadence (Tensilica), videantis, Apical
• A few are sold as chips:
• Analog Devices (PVP), Mobileye, Movidius, TI (EVE)
• Some are do-it-yourself kits:
• For chip designers: Synopsys Processor Designer
• For system designers: Xilinx Zynq
• Challenges:
• Unique programming models and environments
• Limited libraries
• Important (potential) trend: OpenVX
Trend: Vision-Specific (Co-)Processors

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• Different processors are better suited for different applications
• Applications are diverse, and so are processors
• Selecting a processor is a multi-dimensional optimization problem with
incomplete data
• Allow time to evaluate your options
• Macro trend: Increasing industry investment in processors for vision
• Including mobile application processors
• You can benefit by riding on the coattails of high-volume applications
But, progress is uneven and unpredictable  Risk for users
• A processor is only as good as its tools, libraries, etc.
Lessons Learned

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• Processors that are:
• Optimized for vision
• Flexible in I/O options
• Readily available (eval boards, small quantities)
• Easy to program (and optimize for)
• Supported by a roadmap we can be confident in
Wish List

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• “Vision: Promise & Challenge of Heterogeneous Processing,”
http://bit.ly/1rjdBT5
• “Processing Options For Implementing Vision Capabilities in Embedded
Systems,” http://bit.ly/1wq16oW
• “Targeting Computer Vision Algorithms to Embedded Hardware,”
http://bit.ly/1nY2wkD
• “Using Heterogeneous Computing for Mobile and Embedded Vision,”
http://bit.ly/1nY2wkD
Resources