With software teams today twice as large as hardware teams for any given complex SoC project, there is no doubt it is an ideal time to agree on the best way for these worlds to intersect. And even ...

With mask costs for advanced technologies approaching millions of dollars, the simplest mistake can be disastrous. One flaw puts the nonrecurring engineering costs at risk of indeed “never returning, ...

Space Codesign Systems has announced support for ARM‐based FPGA design in its SpaceStudio™ 2.2 virtual platform technology. While we have seen similar announcements from Cadence with Xilinx and ...

Leo managed to sit down with Rajshree Chabukswar, Intel Fellow at Intel Client Computing Group - She works on ...

OpenAI is hiring for a team to "co-design future hardware from different vendors for programmability and performance." In a job listing for the 'HW/SW Co-design Engineer,' the generative artificial ...

Engineers have developed a neuroinspired hardware-software co-design approach that could make neural network training more energy-efficient and faster. Their work could one day make it possible to ...

Hardware/software partitioning algorithms are fundamental in the design of modern embedded systems, where the allocation of functionalities between hardware accelerators and software components is ...

"I was very surprised to see a single TurboQuant algorithm influencing even the hardware and memory markets." Han In-su, a professor in the School of Electrical Engineering at KAIST, said this on the ...

A famous electronics company recently launched a new TV and web commercial emphasizing the importance of designing hardware and software together. (You can view the video here.) It is interesting to ...

There once was a time when system design was completely serial. Entire hardware platforms were designed, prototyped, debugged, and virtually completed before any software development began. Of course, ...

A team led by the University of California San Diego has developed a neuroinspired hardware-software co-design approach that could make neural network training more energy-efficient and faster. Their ...