Ph.D. Dissertations - Kurt Keutzer

Implementing Efficient, Portable Computations for Machine Learning
Matthew Walter Moskewicz [2017]

Exploring the Design Space of Deep Convolutional Neural Networks at Large Scale
Forrest Iandola [2016]

A Framework for Composing High-Performance OpenCL from Python Descriptions
Michael Anderson [2014]

A Framework for Productive, Efficient and Portable Parallel Computing
Ekaterina I. Gonina [2013]

Three Fingered Jack: Productively Addressing Platform Diversity
David Sheffield [2013]

Making computer vision computationally efficient
Narayanan Sundaram [2012]

Parallel Application Library for Object Recognition
Bor-Yiing Su [2012]

Compilation Techniques for Embedded Data Parallel Languages
Bryan Catanzaro [2011]

Parallelism, Patterns, and Performance in Iterative MRI Reconstruction
Mark Murphy [2011]

Pattern-Oriented Application Frameworks for Domain Experts to Effectively Utilize Highly Parallel Manycore Microprocessors
Jike Chong [2010]

Compile Time Task and Resource Allocation of Concurrent Applications to Multiprocessor Systems
Nadathur Rajagopalan Satish [2009]

Task Allocation and Scheduling of Concurrent Applications to Multiprocessor Systems
Kaushik Ravindran [2007]

Automated Mapping of Domain Specific Languages to Application Specific Multiprocessors
William Lester Plishker [2006]

Deploying Concurrent Applications on Heterogeneous Multiprocessors
Andrew Christopher Mihal [2006]

Low Power Design Automation
David Graeme Chinnery [2006]

TIPI: Tiny Instruction Processors and Interconnect
Scott J. Weber [2005]

Programming Models for Application-Specific Instruction Processors
Niraj R. Shah [2004]

Static Crosstalk Noise Analysis for Deep Sub-Micron Digital Designs
Pinhong Chen [2003]