Working Student - Software Developer - Global Static Data Reordering with LLVM

We are seeking a motivated and talented Working Student to undertake a project focused on global and static data reordering using LLVM. This position offers a unique opportunity to work on cutting-edge compiler optimization techniques, enhancing the performance of software systems through data layout transformations. The reordering will be based on CPU performance events, providing a practical and data-driven approach to optimization., * Conduct research and a literature review on static data layout optimization techniques and their impact on program performance.

• Collaborate with compiler engineers to develop a prototype or extend existing LLVM passes for global static data reordering based on CPU performance events.
• Analyze the performance impact of data reordering on various software benchmarks and real-world applications.
• Collaborate with domain experts and supervisors to refine approaches and validate results.
• Document research findings, implementation details, and results comprehensively for thesis submission and possible publication., The Software Team drives customer value by enabling differentiated experiences through leadership AI technologies and foundational software stacks, products, and services. The group is responsible for developing the holistic strategy for client and data center software in collaboration with OSVs, ISVs, developers, partners and OEMs. The group delivers specialized NPU IP to enable the AI PC and GPU IP to support all of Intel's market segments. The group also has HW and SW engineering experts responsible for delivering IP, SOCs, runtimes, and platforms to support the CPU and GPU/accelerator roadmap, inclusive of integrated and discrete graphics., This role will be eligible for our hybrid work model which allows employees to split their time between working on-site at their assigned Intel site and off-site. * Job posting details (such as work model, location or time type) are subject to change.

Do you have a Master's degree?, * Academic Background: Enrolled in a Bachelor's or Master's program in Computer Science, Software Engineering, or a related field.

• Knowledge of LLVM: Prior experience with LLVM or similar compiler frameworks is highly desirable.
• Understanding of Compiler Concepts: Solid grasp of data layout strategies and optimization techniques.
• Analytical Skills: Strong problem-solving abilities with a focus on performance analysis and optimization.Communication: Good written and verbal communication skills for documenting and presenting findings.

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