About

Sruthikesh Surineni is a seasoned Senior Architect with over 9 years of relevant experience in the field of ASIC architecture and micro-architecture, workload characterization, neural networks, and compilers. He is currently working on Machine Learning HW architecture and performance modeling and is passionate about exploring the latest advancements in this field. Prior to his current role at NVIDIA, Sruthikesh worked at Qualcomm, where he was involved in various projects in the Machine Learning group for ML acceleration, performance modeling, and domain-specific compilers. He has also worked on architecture and RTL implementation for ML, computer vision, computer graphics, and video codec acceleration for optimal PPA, successfully taped out multiple ASIC designs. Sruthikesh's specialties include architecture, micro-architecture, HW/SW co-design, performance modeling/estimation, power performance area (PPA) trade-offs, benchmarking, neural networks, machine learning, computer vision, computer graphics, video codec, system on chip architecture, ASIC/FPGA design & verification, RTL - Verilog and System Verilog, synthesis and STA, power analysis (subsystem and chip level), and clock domain crossing analysis. He is proficient in programming languages like C, C++, Python, System Verilog, and CUDA, and has a strong understanding of bus protocols such as AMBA AXI, AHB, APB, and PCIe. Sruthikesh holds a Master’s Degree in Electrical and Computer Engineering from the University of Missouri-Columbia and a Bachelor’s Degree in Electronics and Communication from VIT. His past work experiences include working at Google as an Architecture and Design Engineer, where he was involved in ASIC design and architecture for Datacenter ML acceleration and performance modeling. He also worked at Blaize as a Staff HW Architect/Performance, where he was responsible for SoC architecture research and micro-architecture to accelerate deep learning inference and training. Overall, Sruthikesh is a highly skilled and experienced Senior Architect with a strong background in Machine Learning, Computer Vision, Neural Networks, and Deep Learning. He is passionate about exploring the latest advancements in these fields and enjoys working on challenging projects that require innovative solutions.