苹果System EE-EE/HW Intern (Shanghai)

NVIDIA is developing processor and system architectures that accelerate deep learning and high-performance computing applications. We are looking for an intern deep learning system performance architect to join our AI performance modelling, analysis and optimization efforts. In this position, you will have a chance to work on DL performance modelling, analysis, and optimization on state-of-the-art hardware architectures for various LLM workloads. You will make your contributions to our dynamic technology focused company. What you’ll be doing: • Analyze state of the art DL networks (LLM etc.), identify and prototype performance opportunities to influence SW and Architecture team for NVIDIA's current and next gen inference products. • Develop analytical models for the state of the art deep learning networks and algorithm to innovate processor and system architectures design for performance and efficiency. • Specify hardware/software configurations and metrics to analyze performance, power, and accuracy in existing and future uni-processor and multiprocessor configurations. • Collaborate across the company to guide the direction of next-gen deep learning HW/SW by working with architecture, software, and product teams.

GPU System Architect team’s work scope covers whole GPU pipeline(graphics, compute pipeline, memory system) and multi GPU, CPU and CPU interconnection, which provides good opportunity to deeply learn the latest cross unit new features in the new GPU architectures. The team works as the safety net of the chip. We catch function bugs in the HW by randomly generating tests and running them in various pre-silicon full chip platforms and debugging the failures. This works provides a good full chip view of GPU and has a big space to innovate. What you’ll be doing: • Get familiar with various GPU workload’s composition • Learn about what’s the usual feature metrics for GPU workload • Design and implement inventive solution to efficiently extract features from GPU workload • Verify the solution using direct and random GPU workload • Design and implement inventive solution simplify GPU workload while keeping the required features • Design and implement inventive solution to generate GPU workload according to required features • Design and implement inventive solution to generate GPU workload which has the same feature with a given test and randomize other (required) features • Thoroughly verify the solution on GPU functional simulator/full chip RTL/emulation/silicon platform. • Provide detailed and organized documentation and report out for the project.

• Work proactively on GPU/SOC feature/IP bring-up and characterization including creating validation, tuning and optimization methodologies, develop proper test plan and test cases. • Perform system level use case analysis/profiling and feature return-on-investment investigations, prototype and validation, design methods and control policies to bring the new technology into production and transcend product goals. • Collaborate across System Architecture, DFT, ASIC, SW/FW, platform, validation, and production teams throughout the product life cycle on system-level architecture, design, productization, debugging, and deployment for complex silicon designs to improve quality, safety, and manufacturability. • Design tools/script to automate product definitions, data collection, test case execution, and results analysis. Provide detailed data analysis of functionality, performance, and latency. • Hands on actions on silicon bring-up, validation, and debug; Coordinate product level feature deployment to achieve high product quality at aggressive schedule.

NVIDIA is building the world’s most groundbreaking and state of the art computing platforms for the world to use. NVIDIA NVDLA HW team delivers high quality deep learning accelerator IP to NVIDIA produce lines. Our team’s work includes Deep Learning algorithm, HW architecture/design/verification and SW prototyping.  We are seeking a talented Deep Learning Architecture Engineer to design architecture for innovative deep learning projects and groundbreaking applications such as Gaming, Robotics, and Autonomous Vehicles. You will work with a very brilliant, creative, and helpful team, for a very complex problem that will help to make the world better. What you’ll be doing: • Research, design, and develop architecture solutions of NVIDIA’s accelerating processor • Work on Deep-Learning architecture, algorithms, and software development • Develop function/performance/power models for NVDLA • Co-work with other teams to deliver high quality Deep-Learning processors