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Events for the 2nd week of September
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PhD Defense: Compression of Signal on Graphs with Application to Image and Video Coding
Tue, Sep 05, 2017 @ 04:00 PM - 06:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Workshops & Infosessions
Graph is a generic data structure that is useful in representing signals in various applications. In this thesis, we discuss several transform designs based on graph representation and the application in multimedia compression. Graphs can adapt to local characteristics, e.g. edges, and therefore provide more flexibilities than conventional transforms, e.g. Discrete Cosine Transform(DCT). A frequency interpretation for signal on graphs can be derived using Graph Fourier Transform (GFT). By properly adjusting the graph structure based on signal characteristics, GFT can provide compact representation even for signals with discontinuities. However, the transform requires high complexity in implementation, making it less applicable in signals of large size, e.g. video sequences. In our work, we develop a transform coding scheme based on a low complexity lifting transform on graphs. More specifically, we focus on two problems in the design of lifting transform, namely the design of bipartition and bipartite graph approximation. For the application, we consider two types of multimedia signals, including regular signals on 2D grid and signals that are irregularly distributed. For the former one, we consider the compression of intra-predicted video residuals. The data contain significant edge structures, which are difficult to be represented efficiently with existing transform coding standards. We also discuss different types of edge models for intra and inter-predicted video residuals in terms of the coding efficiency in GFT. For the other type of signal, we discuss the coding scheme for un-demosaicked light field images. Without demosaicking from the raw data captured using Color Filter Array (CFA) to full-color sub-aperture images, we can avoid large redundancies introduced from color interpolation. However, the pixels of each color channel will be distributed irregularly within each sub-aperture image, and therefore motivates the application of graph representation. A novel intra-prediction scheme and graph construction based on sparsely distributed pixels are proposed. Theoretical interpretation and comprehensive experimental results are presented for proposed methods.
More Information: Yung-Hsuan Chao Seminar.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Gloria Halfacre
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Sophomore Info Session
Wed, Sep 06, 2017 @ 04:00 PM - 05:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Workshops & Infosessions
Dear BSEE Sophomores,
You're invited to Meet Your EE Dept. on Wed., Sept. 6 at 4:00 pm in EEB 248.
Delve into the BSEE requirements, undergraduate research opportunities and graduate degrees - PDP and PhD (not too early!). Profs. Maby and Redekopp will be there to answer any questions you have about anything. Meet your advisors.
See you then!
EE Student ServicesLocation: Hughes Aircraft Electrical Engineering Center (EEB) - 102
Audiences: Undergrad
Contact: Benjamin Paul
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Towards Accelerator-Rich Architectures and Systems
Thu, Sep 07, 2017 @ 02:00 PM - 03:15 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Zhenman Fang, UCLA
Talk Title: Towards Accelerator-Rich Architectures and Systems
Abstract: With Intel's $16.7B acquisition of Altera and the deployment of FPGAs in major cloud service providers including Microsoft and Amazon, we are entering a new era of customized computing. In future architectures and systems, it is anticipated that there will be a sea of heterogeneous accelerators customized for important application domains, such as machine learning and personalized healthcare, to provide better performance and energy-efficiency. Many research problems are still open, such as how to efficiently integrate accelerators into future chips and commodity datacenters, and how to program such accelerator-rich architectures and systems.
In this talk, I will first briefly explain how customized accelerators can achieve orders-of-magnitude performance improvement, based on our open-source simulator PARADE [ICCAD 2015, tutorials at ISCA 2015 & MICRO 2016]. Second, I will present our initial work on CPU-accelerator co-design, where we provide efficient and unified address translation support between CPU cores and accelerators [HPCA 2017 Best Paper Nominee]. It shows that a simple two-level TLB design for accelerators plus the host core MMU for accelerator page walking can be very efficient. On average, it achieves 7.6x speedup over the naïve IOMMU and there is only 6.4% performance gap to the ideal address translation. Finally, I will present the open-source Blaze system that provides programming and runtime support to enable easy and efficient FPGA accelerator deployment in datacenters [HotCloud 2016, ACM SOCC 2016]. Blaze abstracts accelerators-as-a-service, and bridges the gap between big data applications (e.g., Apache Spark programs) and emerging accelerators (e.g., FPGAs). By plugging a PCIe-based FPGA board into each CPU server, it can improve the system throughput by several folds for a range of applications.
Biography: Dr. Zhenman Fang is a postdoc in the Computer Science Department, UCLA, working with Prof. Jason Cong and Prof. Glenn Reinman. He is a member of the NSF/Intel funded multi-university Center for Domain-Specific Computing (CDSC) and the SRC/DARPA funded multi-university Center for Future Architectures Research (C-FAR). Zhenman received his PhD in June 2014 from Fudan University, China and spent the last 15 months of his PhD program visiting University of Minnesota at Twin Cities. Zhenman's research lies at the boundary of heterogeneous and energy-efficient computer architectures, big data workloads and systems, and system-level design automation. He has published 10+ papers in top venues that span across computer architecture (HPCA, TACO, ICS), design automation (DAC, ICCAD, FCCM, IEEE Design & Test), and cloud computing (ACM SOCC). He received several awards, including a postdoc fellowship from UCLA Institute of Digital Research and Education, a best paper nominee of HPCA 2017, a best demo award at the C-FAR center annual review. More details can be found in his personal website: https://sites.google.com/site/fangzhenman/.
Host: Xuehai Qian, x04459, xuehai.qian@usc.edu
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Gerrielyn Ramos
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2nd Annual Undergraduate Open House
Fri, Sep 08, 2017 @ 03:00 PM - 05:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Student Activity
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Cathy Huang