I’m excited to share that I’ll be attending SC26 in Chicago!
Taking place November 15–20, 2026, at McCormick Place, SC26 brings together the global high-performance computing community to explore advances in HPC, AI, networking, storage and data-intensive innovation. I look forward to connecting with customers, partners and technology leaders about how these capabilities can accelerate research and help solve complex business challenges.
HPC is a conversation about outcomes
For me, the most interesting HPC conversations begin with the work people need to accomplish: exploring more design alternatives, running scientific simulations, evaluating financial risk or turning growing volumes of data into useful insights.
The opportunity extends beyond adding compute capacity. Organizations also need to get the right resources to the right workloads, manage competing priorities and make powerful infrastructure accessible to the people who depend on it. As AI joins established simulation and analytics workflows, those operational decisions become even more consequential.
Where IBM Spectrum Computing fits
IBM Spectrum Computing is central to the conversations I’m looking forward to in Chicago. Its workload management technologies help organizations coordinate demanding applications across shared computing resources. Two products I’m particularly keen to discuss are IBM Spectrum LSF and IBM Spectrum Symphony.
IBM Spectrum LSF provides workload management and job scheduling for distributed HPC environments. Its policy-driven scheduling, GPU support and hybrid cloud capabilities help teams match workloads to available capacity. For customers balancing simulation, engineering and AI workloads, I want to discuss how scheduling policies can reflect real priorities: urgent work, fair access and productive use of valuable compute resources.
IBM Spectrum Symphony manages compute-intensive and data-intensive distributed applications on a shared grid. It supports resource sharing across applications and hybrid cloud expansion, with use cases that include time-sensitive financial risk and pricing analytics. That creates useful conversations about meeting deadlines while sharing infrastructure across teams and business units.
The practical questions matter as much as the technology: Where does work wait today? Which applications need predictable turnaround? How should teams share resources? When does additional cloud capacity make sense? Those are the discussions that connect HPC architecture to business value.
Bringing HPC, AI and data together
I’m especially interested in how customers are bringing AI into existing HPC environments. Sharing infrastructure introduces questions about GPU access, workload priorities, data movement and the experience of researchers and developers. Effective workload management is an important part of making these environments productive.
The data layer deserves equal attention. Complementing compute and scheduling, IBM Storage Scale provides a high-performance parallel file system for HPC workloads. I look forward to discussing compute and data together, because an application’s path to results depends on both.
The conversations I’m looking forward to
At SC26, I’d love to hear how organizations are improving resource utilization, supporting mixed HPC and AI workloads, and deciding where hybrid cloud fits. I’m also keen to learn how teams measure success—whether that means shorter turnaround times, more experiments completed or a simpler experience for their users.
Across research and industry, the goal is to help people tackle problems that demand more computing power, more data and closer collaboration. SC26 is a chance to exchange practical experience and explore what comes next.
Let’s connect in Chicago
Will you be at SC26? Let’s connect in Chicago to talk about IBM Spectrum Computing, HPC, AI and the challenges you’re working to solve. I look forward to meeting customers, partners and technology leaders, exchanging ideas and exploring new possibilities together.
See you in Chicago, November 15–20!
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Imran Insights
Practical perspectives on AI, DevOps, Engineering Lifecycle Management, HPC and enterprise technology.
