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Copyright © 2014 BDTI 1
Jeff Bier, President, BDTI
May 29, 2014
Trends and Recent Developments in
Processors for Vision
Copyright © 2014 BDTI 2
• 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
Copyright © 2014 BDTI 3
The Fundamental Challenge
High Performance
Low Cost
Low Power
Small
Ease of
Development
(and Optimization)
Flexibility
Copyright © 2014 BDTI 4
Processing Efficiency vs. Development Effort
Performance/$
Performance/W
Development
Effort
Copyright © 2014 BDTI 7
Trend: Heterogeneous Architectures
Performance/$
Performance/W
Development
Effort
Copyright © 2014 BDTI 8
• 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
Copyright © 2014 BDTI 9
• 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
Copyright © 2014 BDTI 10
• 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
Copyright © 2014 BDTI 11
• 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
Copyright © 2014 BDTI 12
• 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
Copyright © 2014 BDTI 13
• “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
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