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Soonhoi Ha

Professor

Seoul National University

South Korea

Research Interests

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About

Dr. Soonhoi Ha is an Associate Professor at Seoul National University, South Korea. His research focuses on processing-in-memory technologies, multi-robot programming frameworks, and optimization methodologies for low-power computer vision systems. He has contributed significantly to areas such as deep learning applications on mobile devices, IoT architectures, and real-time constraints in heterogeneous processing environments.

Articles (20)

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Collaborators (2)

Hoeseok Yang

Santa Clara University

UNITED STATES

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EunJin Jeong

Seoul National University

SOUTH KOREA

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Soonhoi Ha

Research Interests

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About

Articles (20)

Phase-Aware Memory Repartitioning for Extended-Context Edge LLM Inference

TSim4CXL: Trace-Driven Simulation Framework for CXL-Based High-Performance Computing Systems

Empowering Edge Devices With Processing-in-Memory for On-Device Language Inference

A Framework for Multi-Robot Programming: From High-Level Specification to Retargetable Deployment

Pioneering Pathways: The Evolution of Embedded Software Design Methodologies (Keynote)

Software Synthesis From High-Level Specification for Swarm Robotic Applications

Software Optimization and Design Methodology for Low Power Computer Vision Systems

A Novel Throughput Enhancement Method for Deep Learning Applications on Mobile Devices With Heterogeneous Processors

Optimization of Task Allocation for Resource-Constrained Swarm Robots

Software Synthesis From High-level Specification for Swarm Robotic Applications

A novel hierarchical edge-based architecture for service oriented IoT

Energy-Aware Scenario-Based Mapping of Deep Learning Applications Onto Heterogeneous Processors Under Real-Time Constraints

A Novel Technique to Support Deep Learning Applications in a Model-Based Embedded Software Design Methodology

Memory Usage Estimation for Dataflow Model-based Software Development Methodology

Resolution Based Incremental Scaling Methodology for CNNs

SNAS: Fast Hardware-Aware Neural Architecture Search Methodology

Datapath Extension of NPUs to Support Nonconvolutional Layers Efficiently

Multi-Bank On-Chip Memory Management Techniques for CNN Accelerators

Deep Learning Inference Parallelization on Heterogeneous Processors With TensorRT

Adaptive run-time scheduling of dependent services for service-oriented IoT systems

Collaborators (2)

Hoeseok Yang

EunJin Jeong

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