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As we begin to cross the threshold into the billion transistor era Multiprocessor Systems-on-Chips (MPSoC) are becoming ever-present, driving advancement in multiple application domains ranging from entertainment to medical devices. Consequently, MPSoC designers must be able to optimize a multi-constrained set comprised of performance, power consumption, reliability and cost. At the same time, as feature sizes shrink into the sub-micron regime, physical limitations and manufacturing variability are resulting in unreliable, power-hungry chips. To combat this, system simulations which take into consideration the interplay of performance, thermal characteristics, variability, and reliability effects from real-life workloads are becoming valuable when performing design space explorations of these next-generation architectures. However, the increase in complexity stemming from the need to profile complex modern processors, over extended periods of time, is placing a significant burden on the speed of traditional software simulators. | |||||||
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As we begin to cross the threshold into the billion transistor era, Multiprocessor Systems-on-Chips (MPSoC) are becoming ever-present, driving advancement in multiple application domains ranging from entertainment to medical devices. Consequently, MPSoC designers must be able to optimize a multi-constrained set comprised of performance, power consumption, reliability and cost. At the same time, as feature sizes shrink into the sub-micron regime, physical limitations and manufacturing variability are resulting in unreliable, power-hungry chips. To combat this, system simulations which take into consideration the interplay of performance, thermal characteristics, variability, and reliability effects from real-life workloads, are becoming valuable when performing design space explorations of these next-generation architectures. However, the increase in complexity stemming from the need to profile complex modern processors, over extended periods of time, is placing a significant burden on the speed of traditional software simulators. | |||||||
| My work has been motivated by these challenges and has led me to begin investigating a Virtual Platform (ViP) framework on FPGAs which can significantly speed up system profiling through system emulation. Currently, I am working towards building a general framework for the ViP and using it to characterize a multi-core implementation of the IEEE-754 (SPARC V8) architecture. Once in place the ViP will then permit a thorough investigation into alternative architectures and mitigation techniques to achieve the golden "design" polyptych of POWER, PERFORMANCE, RESILIENCY, and COST. | ||||||||
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As we begin to cross the threshold into the billion transistor era Multiprocessor Systems-on-Chips (MPSoC) are becoming ever-present, driving advancement in multiple application domains ranging from entertainment to medical devices. Consequently, MPSoC designers must be able to optimize a multi-constrained set comprised of performance, power consumption, reliability and cost. At the same time, as feature sizes shrink into the sub-micron regime, physical limitations and manufacturing variability are resulting in unreliable, power-hungry chips. To combat this, system simulations which take into consideration the interplay of performance, thermal characteristics, variability, and reliability effects from real-life workloads are becoming valuable when performing design space explorations of these next-generation architectures. However, the increase in complexity stemming from the need to profile complex modern processors, over extended periods of time, is placing a significant burden on the speed of traditional software simulators. My work has been motivated by these challenges and has led me to begin investigating a Virtual Platform (ViP) framework on FPGAs which can significantly speed up system profiling through system emulation. Currently, I am working towards building a general framework for the ViP and using it to characterize a multi-core implementation of the IEEE-754 (SPARC V8) architecture. Once in place the ViP will then permit a thorough investigation into alternative architectures and mitigation techniques to achieve the golden "design" polyptych of POWER, PERFORMANCE, RESILIENCY, and COST. | |||||||
| > > |
As we begin to cross the threshold into the billion transistor era Multiprocessor Systems-on-Chips (MPSoC) are becoming ever-present, driving advancement in multiple application domains ranging from entertainment to medical devices. Consequently, MPSoC designers must be able to optimize a multi-constrained set comprised of performance, power consumption, reliability and cost. At the same time, as feature sizes shrink into the sub-micron regime, physical limitations and manufacturing variability are resulting in unreliable, power-hungry chips. To combat this, system simulations which take into consideration the interplay of performance, thermal characteristics, variability, and reliability effects from real-life workloads are becoming valuable when performing design space explorations of these next-generation architectures. However, the increase in complexity stemming from the need to profile complex modern processors, over extended periods of time, is placing a significant burden on the speed of traditional software simulators. My work has been motivated by these challenges and has led me to begin investigating a Virtual Platform (ViP) framework on FPGAs which can significantly speed up system profiling through system emulation. Currently, I am working towards building a general framework for the ViP and using it to characterize a multi-core implementation of the IEEE-754 (SPARC V8) architecture. Once in place the ViP will then permit a thorough investigation into alternative architectures and mitigation techniques to achieve the golden "design" polyptych of POWER, PERFORMANCE, RESILIENCY, and COST. | |||||||
| In other work I have also developed hardware implementations of Neural Networks and Support Vector Machines as a means for detection and classification within images and video. In this work we utilized FPGA's as the primary means to realize these architectures. | ||||||||
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My research interests include Computer Architectures, Multi-Processor System-on-Chips(MPSoCs), and Field Programmable Gate Arrays(FPGAs). More specifically I am interested in the emulation of future MPSoC Architectures within FPGAs for measuring the golden "design" triptych of POWER, PERFORMANCE, and RELIABILITY. | |||||||
| > > |
As we begin to cross the threshold into the billion transistor era Multiprocessor Systems-on-Chips (MPSoC) are becoming ever-present, driving advancement in multiple application domains ranging from entertainment to medical devices. Consequently, MPSoC designers must be able to optimize a multi-constrained set comprised of performance, power consumption, reliability and cost. At the same time, as feature sizes shrink into the sub-micron regime, physical limitations and manufacturing variability are resulting in unreliable, power-hungry chips. To combat this, system simulations which take into consideration the interplay of performance, thermal characteristics, variability, and reliability effects from real-life workloads are becoming valuable when performing design space explorations of these next-generation architectures. However, the increase in complexity stemming from the need to profile complex modern processors, over extended periods of time, is placing a significant burden on the speed of traditional software simulators. My work has been motivated by these challenges and has led me to begin investigating a Virtual Platform (ViP) framework on FPGAs which can significantly speed up system profiling through system emulation. Currently, I am working towards building a general framework for the ViP and using it to characterize a multi-core implementation of the IEEE-754 (SPARC V8) architecture. Once in place the ViP will then permit a thorough investigation into alternative architectures and mitigation techniques to achieve the golden "design" polyptych of POWER, PERFORMANCE, RESILIENCY, and COST. | |||||||
| In other work I have also developed hardware implementations of Neural Networks and Support Vector Machines as a means for detection and classification within images and video. In this work we utilized FPGA's as the primary means to realize these architectures. | ||||||||
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Michael V. DeBoleMy name is Michael DeBole and I am currently a PhD Candidate in the Department of Computer Science and Engineering at the Pennsylvania State University. I received my B.Sc. degree in Computer Engineering from The Pennsylvania State University in 2006 (with a minor in Engineering Leadership and Development). | ||||||||
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I currently work in the Microsystems Design Laboratory(MDL) within the Computer Science and Engineering Department. My research advisor is Dr. Vijaykrishnan Narayanan. | |||||||
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I currently work in the Microsystems Design Laboratory(MDL) within the Computer Science and Engineering Department. I am co-advised by Dr. Vijaykrishnan Narayanan and Dr. Yuan Xie. | |||||||
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I have an appointment at EPFL for the summer. Please contact me via e-mail.
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My name is Michael DeBole and I am currently a PhD Candidate in the Department of Computer Science and Engineering at the Pennsylvania State University. I recived my B.Sc. degree in Computer Engineering from The Pennsylvania State University in 2006 (with a minor in Engineering Leadership and Development). | |||||||
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My name is Michael DeBole and I am currently a PhD Candidate in the Department of Computer Science and Engineering at the Pennsylvania State University. I received my B.Sc. degree in Computer Engineering from The Pennsylvania State University in 2006 (with a minor in Engineering Leadership and Development). | |||||||
| I currently work in the Microsystems Design Laboratory(MDL) within the Computer Science and Engineering Department. My research advisor is Dr. Vijaykrishnan Narayanan. | ||||||||
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I have an appointment at EPFL for the summer. Please contact me via e-mail. | |||||||
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I am currently a PhD Candidate in the Department of Computer Science and Engineering at the Pennsylvania State University where I work in the Microsystems Design Laboratory(MDL). My research advisor is Dr. Vijaykrishnan Narayanan. | |||||||
| > > |
My name is Michael DeBole and I am currently a PhD Candidate in the Department of Computer Science and Engineering at the Pennsylvania State University. I recived my B.Sc. degree in Computer Engineering from The Pennsylvania State University in 2006 (with a minor in Engineering Leadership and Development). I currently work in the Microsystems Design Laboratory(MDL) within the Computer Science and Engineering Department. My research advisor is Dr. Vijaykrishnan Narayanan. | |||||||
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My research interests include computer architecture and it's integration within signal and image processing. More specifically in the area of pattern classification and computer learning. Recently I have been looking into hardware implementations of neural networks and support vector machines as a means for detection and classification within images and video. I have also been exploring FPGA's as a viable means in which these architectures may be implemented. | |||||||
| > > |
My research interests include Computer Architectures, Multi-Processor System-on-Chips(MPSoCs), and Field Programmable Gate Arrays(FPGAs). More specifically I am interested in the emulation of future MPSoC Architectures within FPGAs for measuring the golden "design" triptych of POWER, PERFORMANCE, and RELIABILITY. In other work I have also developed hardware implementations of Neural Networks and Support Vector Machines as a means for detection and classification within images and video. In this work we utilized FPGA's as the primary means to realize these architectures. | |||||||
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My research interests include computer architecture, embedded systems, and facilitating their use within signal and image processing. More specifically in the area | |||||||
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My research interests include computer architecture and it's integration within signal and image processing. More specifically in the area | |||||||
| of pattern classification and computer learning. Recently I have been looking into hardware implementations of neural networks and support vector machines as a means for detection and classification within images and video. I have also been exploring FPGA's as a viable means in which these architectures may be implemented. | ||||||||
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My research interests include computer architecture and embedded systems. Recently I have been looking into implementing face detection and gender recognition in FPGA's. I am also currenty working on an FPGA implementation of a fast matrix multiplier for scientific computing applications. | |||||||
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My research interests include computer architecture, embedded systems, and facilitating their use within signal and image processing. More specifically in the area of pattern classification and computer learning. Recently I have been looking into hardware implementations of neural networks and support vector machines as a means for detection and classification within images and video. I have also been exploring FPGA's as a viable means in which these architectures may be implemented. | |||||||
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Michael V. DeBoleI am currently a PhD Candidate in the Department of Computer Science and Engineering at the Pennsylvania State University where I work in the Microsystems Design Laboratory(MDL). My research advisor is Dr. Vijaykrishnan Narayanan. | ||||||||
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ResearchMy research interests include computer architecture and embedded systems. Recently I have been looking into implementing face detection and gender recognition in FPGA's. I am also currenty working on an FPGA implementation of a fast matrix multiplier for scientific computing applications. | ||||||||
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Michael V. DeBoleI am currently a PhD Candidate in the Department of Computer Science and Engineering at the Pennsylvania State University where I work in the Microsystems Design Laboratory(MDL). My research advisor is Dr. Vijaykrishnan Narayanan. | ||||||||
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Michael V. DeBoleI am currently a PhD Candidate in the Department of Computer Science and Engineering at the Pennsylvania State University where I work in the Microsystems Design Laboratory(MDL). My research advisor is Dr. Vijaykrishnan Narayanan. | ||||||||
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Michael V. DeBoleI am currently a PhD Candidate in the Department of Computer Science and Engineering at the Pennsylvania State University where I work in the Microsystems Design Laboratory(MDL). My research advisor is Dr. Vijaykrishnan Narayanan. | ||||||||
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My research interests include computer architecture and embedded systems. Recently I have been looking into implementing face detection and gender recognition in FPGA's. I am also currenty working on an FPGA implementation of a fast matrix multiplier for scientific computing applications. | |||||||
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I am currently a PhD Candidate in the Department of Computer Science and Engineering at the Pennsylvania State University where I work in the Microsystems Design Laboratory(MDL). My research advisor is Dr. Vijaykrishnan Narayanan. | |||||||
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I am currently a PhD Candidate in the Department of Computer Science and Engineering at the Pennsylvania State University. I work in the Microsystems Design Laboratory(MDL) within the CSE department where my current research advisor is Dr. Vijaykrishnan Narayanan. I am also the 2006 recipient of the Lockheed Martin Graduate Fellowship. | |||||||
| > > |
My research interests include computer architecture and embedded systems. Recently I have been looking into face detection and its implementation in FPGA's. I am also looking into a FPGA implementation of a fast matrix multiplier for scientific computing applications. | |||||||
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I am currently a PhD Candidate in the Department of Computer Science and Engineering at the Pennsylvania State University. I work in the Microsystems Design Laboratory(MDL) within the CSE department where my current research advisor is Dr. Vijaykrishnan Narayanan. I am also the 2006 recipient of the Lockheed Martin Graduate Fellowship. | |||||||
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