Press release

New Cadence Tensilica Vision Q7 DSP IP Doubles Vision and AI Performance for Automotive, AR/VR, Mobile and Surveillance Markets

Sponsored by Businesswire

Cadence Design Systems, Inc. (NASDAQ: CDNS) today expanded the high end
of its popular Tensilica® Vision DSP product family with the
introduction of the Cadence® Tensilica Vision Q7 DSP
delivering up to 1.82 tera operations per second (TOPS). To address the
increasing computational requirements for embedded vision and AI
applications, the sixth-generation Vision Q7 DSP provides up to 2X
greater AI and floating-point performance in the same area compared to
its predecessor, the Vision Q6 DSP. The Vision Q7 DSP is specifically
optimized for simultaneous localization and mapping (SLAM), a technique
commonly used in the robotics, drone, mobile and automotive markets to
automatically construct or update a map of an unknown environment, and
in the AR/VR market for inside-out tracking. For more information, visit

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The Cadence Tensilica Vision Q7 DSP IP doubles vision and AI performance for the automotive, AR/VR,  ...

The Cadence Tensilica Vision Q7 DSP IP doubles vision and AI performance for the automotive, AR/VR, mobile and surveillance markets. Optimized for simultaneous localization and mapping (SLAM), the Vision Q7 DSP delivers up to 1.82 tera operations per second (TOPS). (Graphic: Business Wire)

Escalating demand for image sensors in edge applications is driving
growth of the embedded vision market. Today’s vision use cases demand a
mix of both vision and AI operations, and edge SoCs require highly
flexible, high-performance vision and AI solutions operating at low
power. In addition, edge applications that include an imaging camera
demand a vision DSP capable of performing pre- or post-processing before
any AI task. While performing SLAM, edge SoCs also require a
computational offload engine to increase performance, reduce latency and
further lower power for battery-operated devices. Because SLAM utilizes
fixed- and floating-point arithmetic to achieve the necessary accuracy,
any vision DSP employed for SLAM must provide higher performance for
both data types.

With its low power and architectural and instruction set enhancements,
the Vision Q7 DSP is ideally suited for the most demanding edge vision
and AI processing requirements and boosts performance for a number of
key metrics:

  • Very long instruction word (VLIW) SIMD architecture delivers up to
    1.7X higher TOPS compared to the Vision Q6 DSP in the same area
  • An enhanced instruction set supporting 8/16/32-bit data types and
    optional VFPU support for single and half precision enables up to 2X
    faster performance on SLAM kernels compared to the Vision Q6 and
    Vision P6 DSPs
  • Delivers up to 2X improvement in floating-point operations per mm2
    (FLOPS/mm2) for both half precision (FP16) and single precision (FP32)
    compared to the Vision Q6 and Vision P6 DSPs
  • Up to 2X greater AI performance in the same area compared to the
    Vision Q6 DSP results in up to 2X improvement in GMAC/mm2
    compared to the Vision Q6 DSP

For AI applications, the Vision Q7 DSP provides a flexible solution
delivering 512 8-bit MACs, compared to 256 MACs for the Vision Q6 DSP.
For greater AI performance, the Vision Q7 DSP can be paired with the
Tensilica DNA 100 processor. In addition to computational performance,
the Vision Q7 DSP boasts a number of iDMA enhancements including 3D DMA,
compression and a 256-bit AXI interface. The Vision Q7 DSP is a superset
of the Vision Q6 DSP, which preserves customers’ existing software
investment and enables an easy migration from the Vision Q6 or Vision P6

“The applications for visual AI are very diverse and are growing very
fast, and these applications have huge appetites for computing
performance. Achieving the required levels of performance with
acceptable cost and power consumption is a common challenge,
particularly as vision is increasingly deployed into cost-sensitive and
battery-powered devices,” said Jeff Bier, founder of the Embedded Vision
Alliance. “I applaud Cadence for its commitment to address this
challenge by developing a series of processing engines tuned for the
needs of visual AI applications.”

“We developed and deployed our AI and vision-based applications on the
past two generations of Cadence Vision DSPs. The 2X increase in both
vision and AI performance provided by the Tensilica Vision Q7 DSP will
be particularly beneficial for SLAM, where low latency is key,”
said Frison Xu, marketing VP at ArcSoft. “This performance increase will
allow us to develop new camera applications including products with
multiple image sensors.”

“Together with Cadence and our customers, we ported our face detection
and vision technology for applications where high performance, low power
and low latency are critical,” said David Shen, senior product marketing
director at Megvii. “Cadence offers one of the best vision and AI
platforms, including the necessary software tools and libraries to
showcase our technology. We look forward to leveraging the Tensilica
Vision Q7 DSP and further solidifying our collaboration with Cadence.”

“For edge computing in our target markets, offloading vision
applications on a high-performance, low-power, highly flexible DSP is a
must,” noted Lazaar Louis, senior director of product management and
marketing for Tensilica IP at Cadence. “Cadence has a long and
successful track record spanning six generations of Vision DSPs, and the
Vision Q7 DSP was designed to address the needs of our key customers
deploying highly complex vision and AI algorithms, including SLAM for
perception. The Vision Q7 DSP strengthens our very successful automotive
portfolio, bringing leading-edge computation to the ‘computer in the
car’ that can be compliant with safety requirements like ISO 26262.”

The Vision Q7 DSP supports AI applications developed in the Caffe,
TensorFlow and TensorFlowLite frameworks through the Tensilica Xtensa®
Neural Network Compiler (XNNC), which maps neural networks into
executable and highly optimized high-performance code for the Vision Q7
DSP. The Vision Q7 DSP also supports the Android Neural Network (ANN)
API for on-device AI acceleration in Android-powered devices, and the
software environment also features complete and optimized support for
more than 1,700 OpenCV-based vision library functions, enabling fast,
high-level migration of existing vision applications. In addition,
development tools and libraries are all designed to enable SoC vendors
to achieve ISO 26262 automotive safety integrity level D (ASIL D)

The Vision Q7 DSP has been sampled to strategic customers and is
expected to be available for general release in the second quarter of

About Cadence

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Design Enablement strategy helps customers develop differentiated
products—from chips to boards to systems—in mobile, consumer, cloud
datacenter, automotive, aerospace, IoT, industrial and other market
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