Why your DL accelerator should be replaced
Intelligence is quickly being added to all our electronics devices. Whether it’s our vehicles that automatically brake when things get dangerous, our phone’s cameras that ensure every picture we take looks great, or our datacenters that need to not just store and distribute our videos, but also understand what’s in them – intelligent image processing using deep learning is everywhere.
But just adding a deep learning accelerator next to a chip’s host CPU subsystem doesn’t mean you have a chip that can handle all the required visual computing tasks. While we’ve seen some designs that didn’t realize this, many SOCs these days do have multiple compute engines for the different imaging-related processing duties.
To read the full article, click here
Related Blogs
- Why You Should Create Your Own NPU Benchmarks
- Why You Can't Trust Your NPU Vendor's Benchmarks
- Mentor Graphics Should Be Acquired or Sold: Carl Icahn
- Mentor Graphics Should Be Acquired or Sold: Carl Icahn COUNTERPOINT
Latest Blogs
- Embedded Security explained: Advanced Encryption Standard (AES)
- Cadence Demonstrates PCIe 8.0 PHY at PCI-SIG DevCon 2026
- Cadence Achieves Successful Silicon Validation of 1st IP Test Chips on Intel 18A
- From Classical CAN and CAN FD to CAN XL: Functional Safety and Security for Next-Generation In-Vehicle Communication
- Accelerating Embedded Memory Performance with 16-bit xSPI PSRAM IP