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Mapping Convolutional Neural Networks to the Vision P5 DSP
Chris Rowen explains how convolutional neural networks (CNNs) map onto the high-performance Tensilica Vision P5 DSP. He describes the benefits that the programmability brings, giving the flexibility needed for the ongoing development of these algorithms alongside the more traditional image processing and computer vision applications.
Posted on Wednesday Feb. 03, 2016
Cadence Channel
Cadence PCIe 4.0 Receiver JTOL Test
1:43
Verification with Emerging Memory Models
4:12
An Introduction to Palladium Cloud
2:04
xSPI Standard Explained
3:42
The Storage Combo PHY IP - Nirvana!
2:41
What is Happening at the USB IF Standards Meetings?
4:03
Cloud-Hosted Design Solution - a Full-Service Cloud Offering
2:37
The Reason Why the Vision Q7 DSP Should be in Your Vision and AI SoC
5:47
Passport Partners Program Expands Customer Cloud Deployment Options
4:36
Cadence Cloud - Fast, Painless, Proven Solutions for Cloud-Based Design
7:08
Cadence PCIe 4.0 Receiver JTOL Test1:43
Verification with Emerging Memory Models4:12
An Introduction to Palladium Cloud2:04
xSPI Standard Explained3:42
The Storage Combo PHY IP - Nirvana!2:41
What is Happening at the USB IF Standards Meetings?4:03
Cloud-Hosted Design Solution - a Full-Service Cloud Offering2:37
The Reason Why the Vision Q7 DSP Should be in Your Vision and AI SoC5:47
Passport Partners Program Expands Customer Cloud Deployment Options4:36
Cadence Cloud - Fast, Painless, Proven Solutions for Cloud-Based Design7:08