Among the many areas of expertise within our research laboratory, we also focused on the efficient implementation of neural networks and their training using advanced compiler techniques. Our work includes optimizing CPU and GPU kernels to improve performance, reduce training time, and increase the scalability of machine learning models. Leveraging principles of systems programming, we also design high-performance machine learning runtimes that ensure efficient resource management and compatibility across diverse hardware, from CPUs and GPUs to specialized accelerators.
This area complements our broader research pursuits in high-performance computing, compiler optimizations, and systems-level innovations aimed at accelerating machine learning and artificial intelligence applications.