המקום בו המומחים והחברות הטובות ביותר נפגשים
What you’ll be doing:
Work with architects and performance architects to develop an energy-efficient GPU.
Develop methodologies and workflows to select and run a wide variety of workloads to train models using ML and/or statistical techniques.
Develop methodologies to improve the accuracy of energy models under various constraints, such as, process, timing, floorplan and layout.
Correlate the predicted energy from models created at different stages of the design cycle, with the goal of bridging early estimates to silicon.
Develop tools to debug energy inefficiencies observed in various workloads run on silicon, RTL and architectural simulators. Work with architects to fix the identified energy inefficiencies.
Work with performance, verification and emulation methodology and infrastructure development teams to integrate energy models into their platforms.
Prototype new architectural features, create an energy model, and analyze the system impact.
What we need to see:
MS degree with 1+ year experience in related fields or equivalent experience
Strong coding skills, preferably in Python, C++.
Background in machine learning, AI, and/or statistical modeling.
Interest in computer architecture and energy-efficient GPU designs.
Familiarity with Verilog and ASIC design principles is a plus.
Ability to formulate and analyze algorithms, and comment on their runtime and memory complexities.
Desire to bring quantitative decision-making and analytics to improve the energy efficiency of our products.
Good verbal/written English and interpersonal skills.
משרות נוספות שיכולות לעניין אותך