Ai Software Architect, Gpu Compute Architecture Team
CurrentI analyze deep learning applications (CNNs, LLMs, GNNs) and create optimal SW mappings to current and future GPU architectures. I find the limiting factors and develop new GPU HW features to breakthrough them. I developed the high level HW architecture for XMX (Intel's matrix accelerator for GPUs), specified the XMX ISA, developed the performance model, and wrote the first convolution and matrix multiply kernels for XMX. I analyzed and modeled a variety of GPU architecture features for deep leaning including structured sparsity, unstructured sparsity, cache policies, pre-fetching, compression, low precision arithmetic, and interconnects.