A wave of machine-learning-optimized chips is expected to begin shipping in the next few months, but it will take time before data centers decide whether these new accelerators are worth adopting and ...

Getting into FPGA design isn’t a monolithic experience. You have to figure out a toolchain, learn how to think in hardware during the design, and translate that into working Verliog. The end goal is ...

Field programmable gate arrays (FPGAs) have emerged as flexible hardware platforms for accelerating deep learning networks, offering high energy efficiency, low latency and reconfigurable parallelism.

Multi-FPGA prototyping of ASIC and SoC designs allows verification teams to achieve the highest clock rates among emulation techniques, but setting up the design for prototyping is complicated and ...

Hardware and device makers are in a mad dash to create or acquire the perfect chip for performing deep learning training and inference. While we have yet to see anything that can handle both parts of ...

Over the last couple of years, the idea that the most efficient and high performance way to accelerate deep learning training and inference is with a custom ASIC—something designed to fit the specific ...

Altera University aims to affordably and easily introduce students to the world of FPGAs and digital logic programming tools by unveiling the curriculum, tutorials, and lab exercises that bridge the ...

Applications and infrastructure evolve in lock-step. That point has been amply made, and since this is the AI regeneration era, infrastructure is both enabling AI applications to make sense of the ...