yli150/openvino

OpenVINO™ Toolkit repository

VictorLi

Summary

• Victor [email protected] is a software architecture of NPU in Intel.
• Victor got his master degree in EE from ZheJiang University, and joined Intel Flex at 2011. Victor started his career from graphics driver and C-for-media runtime development on Intel's GPU.
• From 2018 Q4, Victor has been working for VPU Architecture on various projects, including hardware numeric emulation, neural network low-bit quantization and pruning, vpu performance modelling ..etc.

Work

AI Software Architecture, Intel 2022-Q1 - Present

• AI Software Architecture for multiple generation of Intel NPU product line.
• Focus on compilation technology to run models efficiently on NPU including layer fusion, vertical fusion, operator tiling, scheduling optimization.
• LLM performance optimization, mixed precision, flashattention, task pipeline ..etc.
• Key model performance anlaysis, work with engineering team to identify optimization opportunities and solutions.
• Author of nbperf (5-team-member): is a high level abstract compiler to work with VPU-EM for accurate and reliable model performance simulation.
• Author of numericsbench (3-team-member) : numeric emulation software used for NPU numeric sign-off and validation.
• Academic paper
  • VPU-EM: An Event-based Modeling Framework to Evaluate NPU Performance and Power Efficiency at Scale
  • Neural Architecture Search for Intel Movidius VPU

DeepLearning software Engineer, Intel 2018-Q4 - 2022-Q1

• Neural network quantization and pruning: QAT and Post-training quantization; PACT; Low-bit quantization; Mixed Precision Quantization
• Reinforcement Learning and NAS based approach to search optimal model to fit VPU.
• Academic paper
  • Channel-wise Hessian Aware trace-Weighted Quantization of Neural Networks published by EMC2

Machine Learning Engineer, Intel 2016-06-01 - 2018 Q4

• Focus on deep learning algorithm development on computer vision tasks.
• Led an innovation project "Personal Fitness Coach Powered by AI" incubated by China I2R
• Key developer for chip defects inspection in manufacture.

Senior Graphics Software Engineer, Intel 2011-04-01 - 2016-06-01

• Runtime and User Mode Graphics driver development on multiple mainstream OSes (Linux and Windows)
• Optimized resource management and cross-layer code refactoring
• Cut off 80% validation time by using virtualization technology Worked as a GPGPU (MDF) SDK runtime developer for Intel integrated GPU (from SandyBridge to SkyLake)
• Project open-source link C for Media

Skills

• Master in Computer Vision (Convolutional Neural Network, Human Pose Estimation, Product Defects Detection in Manufacture)
• Master in Graphics Runtime Development (Resource Management, Knowledge on Graphics Subsystem on Windows(DX9/DX11), Graphics software stack on Linux (Libva))
• Master in Programing Languages and Tools (C/C++, Python, Keras, Caffe)

Awards

• Intel ZiZhu Innovation Star 2018

Project

FlexPose: Real-time 2D Human Pose Estimation on CPU 2017-06-01 - 2018-05-01

• Multiple Person 2D Human pose estimation. CNN Network design and optimization.
• Project Introduction Article Get Your AI Fitness Coach
• Selected and incubated by Intel [China I2R Batch 4 Program]
• Numbers： ~4x inference acceleration: depth-wise/separable conv, layer fusion, multiple task learning, clCaffe, fp16, inference engine，30fps at i7-6700HQ

Chip Defects Inspection via CNN 2017-03-01 - 2017-06-01

• Factory faced chip escape with defects on solder-resistor and land pad.
• Traditional CV method can't meet Factory's requirement (false negative and false positive)
• Designed U-shape-like network to do segmentation which outperform detection network.
• Designed image synthesis algorithm to solve limited training sample issue.

Competitions

TianChi FashionAI Cloth KeyPoints Detection 2018

• Competition detect the keypoints of cloth to represent fashion. It contains 5 categories: skirt, blouse, dress, trousers and outwear.
• Keywords: Keras, U-net, GlobalNet+RefineNet, Multiple stack, On line hard negative mining.
• Rank Top2%, 45/2321 at first round competition.

Kaggle Ultrasound Never Segmentation 2016

• Competition try to identify nerve structures in ultrasound images
• Keras, U-net, Dice coefficient loss, Transformation for data augmentation.
• Rank Top5%, 55/923

Kaggle State Farm Distracted Driver Detection 2016

• Competition wants to use CNN to classify driver's behavior, such as texting, drinking, reaching behind during driving.
• Caffe, Fine-tuning from ResNet, Driver location normalization, Data augmentation. Dropout to overcome overfitting.
• Rank Top10%, 132/1440

Education

ZheJiang University - Master in Communication Engineering

• 2011-03-01 - 2008-06-01
• Wireless Sensor Network
• MAC(Media Access Control) Protocol

ZheJiang University - Bachelor in Electronic Information Engineering

• 2002-08-01 - 2006-06-01
• Network
• C Programing Language

Patents

• Apparatus, method, device and medium for accelerating computation of process engine
• Methods and apparatus to accelerate convolution
• Apparatus and method for reinforcement learning based post-training sparsification
• Malware Detection in Memory
• Data Stored or Free Space based Fifo Buffer
• Facilitating Efficient Communication and Data Processing in Heterogeneous Computing Environment in a Heterogeneous Computing Environment
• Event-driven Framework for GPU Programing
• EXECUTION UNIT-SHARED HYBRID TECHNIQUE FOR ACCELERATED COMPUTING ON GRAPHICS PROCESSORS
• Graphics Processing Unit Operation
• GPU-CPU TWO-PATH Memory Copy
• Method and Apparatus to Improve Shared Memory Efficiency
• Apparatus and Method to Improve Memory Access Performance Between Shared Local Memory and System Global Memory

Languages

• Fluent in English
• Native Speaker in Mandarin