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Dive into the research topics where Moinul H. Khan is active.

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Featured researches published by Moinul H. Khan.


international conference on acoustics, speech, and signal processing | 2005

System level adaptive framework for power and performance scaling on Intel/spl reg/ PXA27x processor

Priya N. Vaidya; Moinul H. Khan; Bryan Morgan; Premanand Sakarda

Next generation phone and PDAs face stringent power and performance requirements. In order to take advantage of dynamic voltage and frequency management, software driven adaptive power management methods are emerging as the key to performance and power scaling. This paper demonstrates an adaptive power management framework for Intel XScale/spl trade/ microarchitecture based platforms, which dynamically characterizes executing workloads based on system level events and adapts frequency and voltage in order to save power. In this paper we discuss the overall framework and analysis behind the optimal policy to adapt processor frequency and voltage. The paper also illustrated benefits of using this framework for MP3 playback, memory data transfer, phone idling etc. real life case studies.


signal processing systems | 2005

Accelerating Mobile Video: A 64-Bit SIMD Architecture for Handheld Applications

Nigel C. Paver; Moinul H. Khan; Bradley C. Aldrich; Christopher D. Emmons

Providing quality mobile video applications in hand-held mobile devices requires increased computational capability. Using Single Instruction Multiple Data (SIMD) techniques to expose and accelerate the data parallelism inherent in video processing increases performance in handheld and wireless systems. The paper introduces a new 64-bit SIMD coprocessor of the Intel® XScale® microarchitecture which is optimized for low-power handheld applications. The architecture blends the SIMD media processing style with the capabilities of the XScale microarchitecture. This paper provides an overview of the architecture, its instruction set, programming model, the pipeline organization and functional units. The paper also describes how key features of architecture improve the performance of video applications as compared to a scalar implementation. The performance and power improvements based upon measured results are analyzed to show how the opportunities of power savings by reducing the frequency and voltage can be realized.


international symposium on multimedia | 2004

Accelerating Mobile Multimedia with Intel Wireless MMX Technology

Nigel C. Paver; Moinul H. Khan; Bradley C. Aldrich

Demand for mobile video applications is growing today in wireless handheld platforms. Intel/spl reg/ Wireless MMX/spl trade/ technology has been designed to accelerate mobile multimedia and applications processing in a power efficient manner. Optimizing instruction set architecture is a logical approach towards attaining higher performance in multimedia applications. Wireless MMX technology is a 64-bit single instruction multiple data, (SIMD), coprocessor for the Intel/spl reg/ Xscale/spl reg/ microarchitecture. This paper provides an overview of Wireless MMX technology and the key features of the architecture that specifically enhance the multimedia performance. Tools and techniques for optimization are also described.


international conference on acoustics, speech, and signal processing | 2003

Intel/spl reg/ wireless MMXTM technology: a 64-bit SIMD architecture for mobile multimedia

Nigel C. Paver; Bradley C. Aldrich; Moinul H. Khan

The growing demand for multimedia rich applications in the wireless mobile domain challenges the capabilities of current wireless handheld devices. Optimizing instruction set architecture is a logical approach towards attaining higher performance in multimedia applications. Intel/spl reg/ wireless MMXTM technology is a 64-bit single instruction multiple data, (SIMD), coprocessor for the Intel/spl reg/ XScale/spl trade/ microarchitecture. It accelerates multimedia applications in handheld and wireless devices by taking advantage of the inherent parallelism and data types of targeted applications. This paper provides an overview of the wireless MMX architecture, its instruction set, pipeline organization, and functional units. Initial benchmark results measured on silicon are also presented.


Multimedia Tools and Applications | 2006

Optimizing mobile multimedia using SIMD techniques

Nigel C. Paver; Moinul H. Khan; Bradley C. Aldrich

Demand for mobile video applications is growing today in wireless handheld platforms. Optimizing instruction set architectures and employing SIMD techniques is a logical approach towards attaining higher performance in mobile multimedia applications. Intel® Wireless MMX™ technology has been designed to accelerate mobile multimedia and applications processing in a power efficient manner. This paper provides an overview of Intel® Wireless MMX™ technology, a 64-bit Single Instruction Multiple Data (SIMD) coprocessor for the Intel® XScale® microarchitecture, and the key features of the architecture that specifically enhance the multi-media performance. Tools and techniques for optimization are also described.


international conference on acoustics, speech, and signal processing | 2007

Time Series Modeling Based Power and Performance Scaling Framework

Moinul H. Khan; Yu Bai; Bin Xiao; Priya N. Vaidya

This paper enhances a software based framework to dynamically scale power and performance with high accuracy in a resource limited embedded system, like cellular phones and PDAs. Key challenges for such a framework are accurate forecasting of dynamic resource demands inherent in the workloads. In this paper we describe three innovative methods: (1) smart forecast method based on linear and non-linear filtering models; (2) policy decision based on high fidelity memory and computation characterization; and (3) adaptive sampling period to adapt to dynamic changes in the workloads. Power and performance framework driven by the proposed algorithms reduces power consumption thus improving battery lifetime for the end-user.


international conference on consumer electronics | 2007

A Highly Accurate Power And Performance Scaling Framework in An Embedded Environment

Moinul H. Khan; Yu Bai; Bin Xiao; Priya N. Vaidya

This paper enhances a software based framework to dynamically scale power and performance with high accuracy in a resource limited embedded system, like cellular phones and PDAs. Key challenges for such a framework are accurate forecasting of dynamic resource demands inherent in the workloads. In this paper we describe two innovative methods: (1) smart forecast method based on linear and non-linear filtering models and (2) adaptive sampling period to adapt to dynamic changes in the workloads. Power and performance framework driven by the proposed algorithms reduces power consumption thus improving battery lifetime for the end-user.


signal processing systems | 2003

Accelerating mobile video applications using Intel/sup /spl reg// Wireless MMX/spl trade/ technology

Nigel C. Paver; Moinul H. Khan; Bradley C. Aldrich; Christopher D. Emmons

Demand for mobile video applications is growing today in wireless handheld platforms. Intel/sup /spl reg// Wireless MMX/spl trade/ technology has been designed to accelerate video applications by using single instruction multiple data (SIMD) techniques to expose and accelerate the data parallelism inherent in video processing. Intel Wireless MMX technology is a 64-bit SIMD coprocessor of the Intel XScale/spl trade/ microarchitecture which is optimized for low-power handheld applications. The paper provides an overview of the Wireless MMX technology architecture, its instruction set, pipeline organization and functional units. It also provides analysis of the features of the architecture that specifically enhance the video performance. Initial measured performance results are also provided.


Archive | 2003

Securing an electronic device

Tayib Sheriff; Minda Zhang; Moinul H. Khan; David M. Wheeler; John P. Brizek; Mark N. Fullerton


Archive | 2009

Method and apparatus for a trust processor

Moinul H. Khan; David M. Wheeler; John P. Brizek; Anitha Kona; Mark N. Fullerton

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