Cliff Sze
His research interests include optimization and the analysis of algorithms.
Authored Publications
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Fast and Highly Scalable Bayesian MDP on a GPU Platform
He Zhou
Sunil P. Khatri
Jiang Hu
Frank Liu
ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM BCB), ACM (2017)
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By employing Optimal Bayesian Robust (OBR), Bayesian Markov
Decision Process (BMDP) can be a power optimization method to
solve large problems. However, due to the “curse of dimensionality”,
the data storage limitation hinders the practical application of
BMDP. To overcome this impediment, we propose a novel Improved
Compressed Sparse Row (ICSR) data structure in this paper, and developed
the implementation of BMDP solver with ICSR technique
on a heterogeneous platform with GPU. The simulation results
demonstrate that our techniques achieve about a 5× reduction in
memory utilization over using full matrix, and an average speedup
of 4.1× over using full matrix. Additionally, we present a study of
the tradeoff between the runtime and the trends of result di fference
between our ICSR techniques and using full matrix.
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Large-Scale 3D Chips: Challenges and Solutions for Design Automation, Testing, and Trustworthy Integration
Johann Knechtel
Ozgur Sinanoglu
Ibrahim (Abe) M. Elfadel
Jens Lienig
IPSJ Trans. System LSI Design Methodology (2017)
Preview abstract
Three-dimensional (3D) integration of electronic chips has been advocated by both industry and academia
for many years. It is acknowledged as one of the most promising approaches to meet ever-increasing demands on
performance, functionality, and power consumption. Furthermore, 3D integration has been shown to be most effective
and efficient once large-scale integration is targeted for. However, a multitude of challenges has thus far obstructed
the mainstream transition from “classical 2D chips” to such large-scale 3D chips. In this paper, we survey all popular
3D integration options available and advocate that using an interposer as system-level integration backbone would
be the most practical for large-scale industrial applications and design reuse. We review major design (automation)
challenges and related promising solutions for interposer-based 3D chips in particular, among the other 3D options.
Thereby we outline (i) the need for a unified workflow, especially once full-custom design is considered, (ii) the current
design-automation solutions and future prospects for both classical (digital) and advanced (heterogeneous) interposer
stacks, (iii) the state-of-art and open challenges for testing of 3D chips, and (iv) the challenges of securing hardware in
general and the prospects for large-scale and trustworthy 3D chips in particular.
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