This is where verification teams can spend vast efforts in simply managing the necessarily high volumes of testing required to achieve QOR and meet test plan and coverage goals.
Ask any seasoned verification engineer how much time they spend setting up regressions, and aligning the compute and storage needs to the job types, and then nursing the regressions through to completion, often with many out-of-hours interventions. This is followed by time-consuming triaging of the results to identify the root causes of failure, analyzing failure signatures, and identifying those jobs that need to be re-run for full debug and investigation.
There can be a lot of wasted compute-intensive resources, which has a direct impact on verification cost. When submitting large batch regressions to the job queue, any failed jobs that are not recognized early enough might unnecessarily consume compute hours or storage capacity. In addition, regressions that are repeatedly run on the same codebase with the same conditions are unlikely to stimulate new paths and expose new bugs.
Sometimes, with an on-prem environment, verification engineers become infrastructure and resource managers. They need a detailed understanding of their compute and storage environments to ensure they are using the best resources for each job type, tuning the requirements to optimize turnaround time and infrastructure costs. They are often competing for resources with other teams that are sharing finite resources. With fixed resources your TTR depends on the width of your execution pipeline and the speed and efficiency of the compute resources. The turnaround time may be predictable, but what difference would it make to your development lifecycle and the effectiveness of your engineering team, if you could significantly reduce TTR with a wider and faster execution pipeline? The total resource consumption may be the same or less (because of improved efficiencies of the infrastructure), but engineers gain a productivity uplift as they can respond to and validate design changes more quickly, enabling more iterations. This, in turn, enables the engineering team to deliver a higher quality product. It could be a game-changer.
The Synopsys Cloud Verification Instance integrates VC Execution Manager to deliver efficient regression automation and high productivity in the cloud. This fully integrated environment ensures that the user can focus on the verification task and is not burdened with cloud job management. Cloud Verification Instance takes care of all job execution details such as executing simulations, merging coverage, invoking Synopsys Verdi® Automated Debug System for debug and generation of reporting and analytics. Synopsys cloud portal provides an option to provision dynamic clusters which have an ability to auto-start or stop dynamically based on a pre-set idle time (5 minutes) and auto starts when jobs are submitted to that queue.