Real-Time and Energy-Efficient Face Detection on CPU-GPU Heterogeneous Embedded Platforms

Runtime specialization for heterogeneous CPU-GPU platforms

Energy-Aware Real-Time Face Recognition System on Mobile CPU-GPU Platform

The Graphics Processor Unit (GPU) has expanded its role from an accelerator for rendering graphics into an efficient parallel processor for general purpose computing. The GPU, an indispensable component in desktop and server-class computers as well as game consoles, has also become an integrated component in handheld devices, such as smartphones. Since the handheld devices are mostly powered by...

Heterogeneous Sparse Matrix Computations on Hybrid GPU/CPU Platforms

Hybrid GPU/CPU clusters are becoming very popular in the scientific computing community, as attested by the number of such systems present in the Top 500 list. In this paper, we address one of the key algorithms for scientific applications: the computation of sparse matrix-vector products that lies at the heart of iterative solvers for sparse linear systems. We detail how design patterns for sp...

Protecting Real-Time GPU Applications on Integrated CPU-GPU SoC Platforms

Integrated CPU-GPU architecture provides excellent acceleration capabilities for data parallel applications on embedded platforms while meeting the size, weight and power (SWaP) requirements. However, sharing of main memory between CPU applications and GPU kernels can severely affect the execution of GPU kernels and diminish the performance gain provided by GPU. For example, in the NVIDIA Jetso...

Optimization Techniques for Mapping Algorithms and Applications onto CUDA GPU Platforms and CPU-GPU Heterogeneous Platforms

Title of dissertation: OPTIMIZATION TECHNIQUES FOR MAPPING ALGORITHMS AND APPLICATIONS ONTO CUDA GPU PLATFORMS AND CPU-GPU HETEROGENEOUS PLATFORMS Jing Wu, Doctor of Philosophy, 2014 Dissertation directed by: Professor Joseph F JaJa, Department of Electrical and Computer Engineering An emerging trend in processor architecture seems to indicate the doubling of the number of cores per chip every ...