EDA moves to the cloud

December 28, 2020 // By Nick Flaherty
EDA moves to the cloud
The move to the cloud for EDA accelerated through 2020. Nick Flaherty looks back over a key year for chip development, from digital twin models to quantum computing

If you are an engineer of a certain age, you will remember for ‘engineering workstation’. Those high cost, high performance machines were in short supply and were used to run the leading edge electronic design automation (EDA) tools.

But the workstation also drove chip and graphics architecture. Silicon Graphics drive the MIPS architecture (and was subsumed into Cray and now HP Enterprise), Sun Microsystems had its own Sparc architecture before the takeover by Oracle, and Digital Equipment (DEC, RIP) had its ARM-based Alpha chip, developed by a team that went on to Apple and arguably has resulted in the M1 chip powering the latest Macbook.

However, these mighty machines (for their time) were overtaken by the network. Client-server architectures allowed higher performance servers to run the EDA tools.

These servers were consolidated into server farms, with racks of processors on-site, and now we are seeing the next stage in the evolution into the cloud.

The ‘big three’ Eda suppliers have had cloud in their strategic roadmaps for several years, and this work has come to fruition this year. Earlier this month, ARM showed the importance of the cloud.

“Arm is moving the majority of its EDA workloads to AWS as part of our effort to reduce our global datacentre footprint by at least 45% and our on-premises compute capabilities by 80% as we complete our migration to AWS,” said Rene Haas, President of thee IP Group at Arm. “We have already realized a 6x improvement in performance time for EDA workflows on AWS and see the potential for increasing throughput by 10x.”

As part of this move, AWS used the VCS Fine-Grained Parallelism (FGP) technology from Synopsys running on Arm-based Graviton2 servers. This enables accelerated development and verification of breakthrough connectivity technology and SoCs.

Next: Digital twin EDA 

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