Research Area

Systems Research

We focus on extending the frontiers of machine learning and AI by developing novel algorithmic, software and hardware techniques.

Our areas of research include computer languages, compilers, low-level optimization, distributed and parallel computing, computer arithmetic, HPC, GPU/FPGA/ASIC hardware applications, and HW/SW co-design.

Latest Publications

Systems Research
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Rethinking floating point for deep learning

We improve floating point to be more energy efficient than equivalent bit width integer hardware on a 28 nm ASIC process while retaining accuracy in 8 bits with a novel hybrid log multiply/linear add, Kulisch accumulation and tapered encodings from Gustafson's posit format.

Systems Research
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Billion-scale similarity search with GPUs

Similarity search finds application in specialized database systems handling complex data such as images or videos, which are typically represented by high-dimensional features and require specific indexing structures. This paper tackles the problem of better utilizing GPUs for this task.

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