This article first appeared in DigiTimes, June 5th, 2025 and is translated and republished with the permission of DigiTimes.
As a global leader in NAND flash memory controllers, Silicon Motion’s solutions are widely deployed across consumer electronics—including PCs, smartphones, and gaming consoles—as well as in data centers, enterprise-grade storage, AIoT, automotive systems, and industrial control applications.
To address the increasingly complex demands of next-generation IC design and maximize computing resource efficiency, Silicon Motion has partnered with Makoto Technology to deepen the integration of IBM LSF (Load Sharing Facility). This initiative includes the deployment of advanced resource monitoring modules, optimization of scheduling logic, and the establishment of cross-functional collaboration frameworks—resulting in significant improvements in R&D productivity and system-wide visibility.
Silicon Motion Sets Out to Optimize Scheduling Efficiency Implementing LSF to Optimize Computing Resource Management
Guo Mingyue, Information Department Manager at Silicon Motion, noted that prior to LSF implementation, server resources were manually allocated, leading to uneven distribution, low utilization rates, and limited responsiveness to large-scale simulation demands.
To overcome these challenges, Silicon Motion adopted IBM LSF—a mature and widely adopted solution in the IC design industry. LSF supports distributed scheduling across extensive compute resources and integrates seamlessly with a broad range of EDA tools.
Simultaneously, the company introduced the IBM LSF RTM (Report, Monitor, Track), which delivers real-time, visualized reports on resource consumption. RTM enables predictive analytics for resource planning over 6–12 months and leverages algorithms to forecast usage trends.
Kuo Mingyue commented that according to performance metrics, the adoption of LSF has led to a marked increase in compute resource utilization—from 60–70% previously to 80–90%, with peaks exceeding 90% during critical periods. This has translated into faster access to computing resources for R&D teams, significantly reducing wait times and accelerating design simulation and verification cycles.
The RTM module further empowers management with granular insights into CPU core usage, time allocation, and workload spikes across projects. These insights support annual resource planning, post-project analysis, performance evaluation, and budget optimization.
From a Total Cost of Ownership (TCO) perspective, LSF has enabled more efficient use of server infrastructure and EDA licenses, reducing hardware investments and labor costs while maximizing operational efficiency.
Strengthening IT Governance and Cross-Departmental Collaboration
The unified scheduling platform and visual reporting tools have enhanced IT governance and interdepartmental coordination. With transparent data and objective metrics, IT teams can align resource allocation with R&D needs, minimizing duplication and improving decision-making legitimacy and collaboration efficiency.
Silicon Motion and Makoto: Building a Foundation for Intelligent Computing
Prior to system deployment, Silicon Motion invested heavily in internal alignment with R&D stakeholders. Post-implementation, the tangible benefits of the platform have fostered internal trust and consensus. Makoto Technology played a pivotal role throughout this transformation.
Despite not being the original developer of LSF, Makoto was selected for its deep expertise in both HPC and EDA domains, its familiarity with Silicon Motion’s organizational culture, and its proven track record of successful LSF deployments. Guo highlighted Makoto’s responsiveness, service quality, and ability to translate technical requirements between IT and R&D teams.
Makoto Chairman Su Yibin emphasized the company’s commitment to a “Trust Model,” built on integrity and long-term partnerships. He noted that LSF requires dual-domain expertise, and Makoto’s ability to bridge HPC and EDA has made it a preferred partner for many IC design firms. The company also fosters a collaborative user community through annual training programs, enhancing customer engagement and loyalty.
Looking Ahead
The partnership between Silicon Motion and Makoto Technology not only addresses the enterprise’s internal challenges in computing resource management but also exemplifies how Taiwan’s semiconductor and IC design sectors are leveraging digital tools to drive operational excellence and industry-wide transformation.
While Silicon Motion has already achieved a resource utilization rate of 80–90%, the company remains committed to further optimizing its R&D platform and computing resource efficiency. This includes dynamic adjustments based on project phases and tool-specific requirements to ensure peak performance and a stable operating environment.
Makoto Technology will continue its strategic collaboration with Silicon Motion, focusing on deeper integration of RTM reporting and AI-driven models. These enhancements aim to enable real-time forecasting and automated analysis, laying the foundation for a more intelligent and adaptive resource management system.
Guo Mingyue emphasized that in the era of AI, selecting solutions that address both current operational needs and future innovation trajectories is critical to maintaining competitive advantage. The combined capabilities of IBM Spectrum LSF and Makato’s technical expertise have played a pivotal role in elevating Silicon Motion’s R&D efficiency and operational agility.