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Akash Kumar (1980-)

Informatiker

Name	Akash Kumar
Time	1980- (Date of birth and death)
Place	Bijnor (Geburtsort) Niederlande Singapur Deutschland
Academic degree	Dr.
Profession	Informatiker (characteristic profession)
Related	Technische Universität Dresden Technische Universiteit Eindhoven National University of Singapore
Further information	Bachelor in Computer Engineering, National Univ. of Singapore, Master in Technological Design (Embedded Systems), Eindhoven Univ. of Technology
Record type	Person
GND-Identifier	143247042
Record ID	143247042
Involved in show all Adaptive Techniques for Efficient Embedded Deep Learning Towards efficient ultra low-bitwidth neural networks: A systematic study of architecture design, training optimization and deployment Design of Energy-Efficient and High-Throughput Reconfigurable Systems through Cross-Layer Approximation Efficient Neural Network Inference on Resource-Constrained Devices Understanding and Quantifying Confidence in Individual Machine Learning Predictions Peak-Power Aware Lifetime Reliability Improvement in Fault-Tolerant Mixed-Criticality Systems Post-Training Optimization of Cross-layer Approximate Computing for Edge Inference of Deep Learning Applications Quality-of-Service Aware Design and Management of Embedded Mixed-Criticality Systems A Hardware/Software Stack for Heterogeneous Systems Architecture and Advanced Electronics Pathways Toward Highly Adaptive Energy- Efficient Computing Database System Acceleration on FPGAs Analytical Exploration and Quantification of Nanowire-based Reconfigurable Digital Circuits Design Automation and Application for Emerging Reconfigurable Nanotechnologies Design, Analysis, and Applications of Approximate Arithmetic Modules Methods and Tools for Battery-free Wireless Networks Quality-of-Service Aware Design and Management of Embedded Mixed-Criticality Systems A Physical Synthesis Flow for Early Technology Evaluation of Silicon Nanowire based Reconfigurable FETs Reliable and Energy Efficient Streaming Multiprocessor Systems An Automated Flow to Map Throughput Constrained Applications to a MPSoC

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Katalog der Deutschen Nationalbibliothek

Akash Kumar (1980-)

Adaptive Techniques for Efficient Embedded Deep Learning

Towards efficient ultra low-bitwidth neural networks: A systematic study of architecture design, training optimization and deployment

Design of Energy-Efficient and High-Throughput Reconfigurable Systems through Cross-Layer Approximation

Efficient Neural Network Inference on Resource-Constrained Devices

Understanding and Quantifying Confidence in Individual Machine Learning Predictions

Peak-Power Aware Lifetime Reliability Improvement in Fault-Tolerant Mixed-Criticality Systems

Post-Training Optimization of Cross-layer Approximate Computing for Edge Inference of Deep Learning Applications

Quality-of-Service Aware Design and Management of Embedded Mixed-Criticality Systems

A Hardware/Software Stack for Heterogeneous Systems

Architecture and Advanced Electronics Pathways Toward Highly Adaptive Energy- Efficient Computing

Database System Acceleration on FPGAs

Analytical Exploration and Quantification of Nanowire-based Reconfigurable Digital Circuits

Design Automation and Application for Emerging Reconfigurable Nanotechnologies

Design, Analysis, and Applications of Approximate Arithmetic Modules

Methods and Tools for Battery-free Wireless Networks

Quality-of-Service Aware Design and Management of Embedded Mixed-Criticality Systems

A Physical Synthesis Flow for Early Technology Evaluation of Silicon Nanowire based Reconfigurable FETs

Reliable and Energy Efficient Streaming Multiprocessor Systems

An Automated Flow to Map Throughput Constrained Applications to a MPSoC