Chip-making expert Advanced Micro Devices has planned to shift its workload of electronic design automation to Google Cloud to achieve better performance and flexibility
Google Cloud and AMD have announced a groundbreaking collaboration of electronic design automation (EDA) for the chip design workload of AMD. In this partnership, the AMD will operate these automation processes on Google Cloud to prolong its capabilities of on-premises data centers.
EDA is a vital element of the chip design process, including computer-equipped software designs to develop printed and integrated circuit boards and microprocessors. Chipmakers need complicated designs to merge parts onto the circuit board at intense density, and EDA has provided standardized operations and smooth automation to aid in prompt development.
AMD to leverage advanced cloud services from Google
The chipmakers can easily create, plan, model, and test new circuit designs to analyze their performance and address any potential roadblocks before production by utilizing the EDA software.
Given the remarkability of EDA, it’s pretty easy to comprehend why AMD prefers to run its workloads on Google Cloud. The company mentioned that AMD would leverage Cloud’s massive storage, modern networking, and artificial intelligence ability.
The GM and VP of Infrastructure at Google Cloud, Sachin Gupta, has shared his views on this partnership by saying:
“In today’s semiconductor environment, the speed, scale, and security of the cloud unlock much-needed flexibility. We are pleased to provide the infrastructure required to meet AMD’s compute performance needs and equip the company with our AI solutions to continue designing innovative chips.”
The elasticity, scale, and efficient usage of resources contribute to chip design, especially given the surge in computer processing which grows with node advancement. AMD also plans to utilize the latest compute-optimized C2D VMI of Google Cloud powered by its own 3rd Gen AMD EPYC processors.
By using these resources from Google Cloud, AMD expects to run and operate more designs in correspondence, allowing maximum flexibility to manage its short-term compute demand without lowering the allocation of resources on long-term projects.