"Revolutionary Methods Turbocharge Sparse Tensors in AI's Massive Models"
Researchers from MIT and NVIDIA have developed two techniques to accelerate the processing of sparse tensors, a type of data structure used in high-performance computing tasks. The first technique, called HighLight, allows hardware accelerators to efficiently find nonzero values for a wider variety of sparsity patterns, resulting in better energy efficiency. The second technique, called Tailors and Swiftiles, maximizes the utilization of on-chip memory by effectively "overbooking" the tile size, reducing off-chip memory traffic and improving processing speed. Both methods enhance the performance and energy efficiency of hardware accelerators used in massive AI models.