Potential internships require research experience in at least one of the following areas:
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Chip-level and System-level Architecture
GPU and Multi-GPU Architecture Scalable memory systems and new memory technologies
Scalable on-chip and off-chip interconnects
Chip-level and system-level scheduling
Power, performance, and energy-efficiency in large-scale systems
Specialized accelerators for workloads like AI algorithms, crypto algorithms, databases, etc.
Hardware-software co-design
Systems Infrastructure for large LLM training and inference
Systems/AI algorithms codesign (e.g., for sparsity) \
AI/ML for systems (hardware design, code optimization, etc.)
GPU-accelerated algorithms
Languages and programming models for parallel computing
Optimizing compilers and AI-based performance assistants
Distributed runtime systems
Systems software and operating system interfaces
Optimizing GPU-accelerated workloads
Compilers and code verification
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High-Performance Networking and Interconnects
Large-scale GPU networking
Topologies, routing, and congestion control
Networking techniques at the intersection of scale-out and scale-up
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VLSI and Electronic Design Automation (EDA)