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Short-running Jobs Can Help Optimize Your Resource Utilization

Semiconductor companies typically run jobs by queuing them up, then using a job scheduler to dispatch them onto available cores in server farms while pulling EDA tool licenses from a license server. There are two primary goals facing organizations, and they’re somewhat at odds with each other: first, maximizing the utilization of server farms and software licenses and second, running jobs with minimal latency so users aren’t delayed.

The easiest way to satisfy the requirements of high utilization and low latency is to maximize the number of short-duration jobs. Just as it is easier to fill a bucket with sand than it is with large rocks, short jobs give the scheduler increased flexibility in what jobs to run and when. Short jobs will not block or occupy a resource for long periods and are therefore not likely to impede the progress of higher-priority jobs arriving in the queue.

Altair Accelerator™ is an agile, fully featured scheduler optimized for today’s EDA workloads. The most important difference between Accelerator and other popular schedulers is its event-driven architecture, which allows it to schedule a new job immediately when compute resources and software licenses become available.

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Meeting Job Scheduling Challenges for Organizations of All Sizes

Every semiconductor design group uses some sort of job scheduler, whether it is selected by a corporate IT department or by the group itself. At a high level, the function of a job scheduler is simple: Be aware of what is in the queue and what hardware and software license resources are available and make good decisions about what jobs to schedule when. In practice there are a several subtle issues that are just as important, including job mix, prioritization, and ease of support. While every company is unique, the issues surrounding job scheduling are often related to company size or, more accurately, the size of the compute farm and design teams. Altair Accelerator™ is a high-throughput, enterprise-grade job scheduler designed to meet the complex demands of semiconductor design, EDA, and high-performance computing (HPC). It’s a highly adaptable solution capable of managing compute infrastructures from small, dedicated server farms to complex, distributed environments.

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A Cost-benefit Look at Open-source vs. Commercial HPC Workload Managers

High-performance computing (HPC) fuels scientific discovery and innovation across multiple industries. The combination of large datasets, advanced simulation techniques, and machine learning helps organizations generate insights that would not be possible without modern HPC infrastructure. Given HPC’s outsized role in driving business results, selecting the right management software is critical. This is especially true in commercial organizations where time is money. In this paper, we discuss the pros and cons of open-source software in HPC and make the case for commercial workload management. While open-source workload managers are fine in some situations, they can present disadvantages in production environments.

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Six Smarter Scheduling Techniques for Optimizing EDA Productivity

Semiconductor firms rely on software tools for all phases of the chip design process, from system-level design to logic simulation and physical layout. Given the enormous investment in tools, design talent, and infrastructure, even minor improvements in server farm efficiency can significantly impact the bottom line. As a result, verification engineers and IT managers are constantly looking for new sources of competitive advantage. Workload management plays a crucial role in helping design teams share limited resources, boost simulation throughput, and maximize productivity. In this paper, we discuss six valuable techniques to help improve design center productivity.

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