Abstract—Modern processors crudely manage thermal emergencies through Dynamic Thermal Management ... more Abstract—Modern processors crudely manage thermal emergencies through Dynamic Thermal Management (DTM), where the processor monitors the die temperature and dynamically adjusts the processor voltage and frequency (DVFS) to throttle down the processor when necessary. However, DVFS tends to yield marked degradation in both application performance and system reliability.
Abstract Reliable remote measuring of flow meters for the petroleum gas industry is proposed in t... more Abstract Reliable remote measuring of flow meters for the petroleum gas industry is proposed in this work. The monitoring of flow rates and the total amount of the fluid flow is collected using a manual process. The main goal of this work is to implement a mechanism that avoids human error and achieves reliable, continuous, and accurate monitoring.
Abstract This article proposes a runtime model that relates server energy consumption to its over... more Abstract This article proposes a runtime model that relates server energy consumption to its overall thermal envelope, using hardware performance counters and experimental measurements. While previous studies have attempted system-wide modeling of server power consumption through subsystem models, our approach is different in that it links system energy input to subsystem energy consumption based on a small set of tightly correlated parameters.
Abstract The discovery and management of energy resources, especially at locations in the Gulf of... more Abstract The discovery and management of energy resources, especially at locations in the Gulf of Mexico, requires an economic but technically enhanced infrastructure. Research teams from Louisiana State University, University of Louisiana at Lafayette, and Southern University Baton Rouge are engaged in a collaborative effort to create a ubiquitous computing and monitoring system (UCoMS) for the discovery and management of energy resources.
This paper proposes a chaotic time series model of server system- wide energy consumption to capt... more This paper proposes a chaotic time series model of server system- wide energy consumption to capture the dynamics present in ob- served sensor readings of underlying physical systems. Based on the chaotic model, we have developed a real-time predictor that es- timates actual server energy consumption according to its overall thermal envelope. This chaotic time series regression model relates processor power, bus activity, and system ambient temperatures for real-time prediction of power consumption during job execution to enable run-time control of their thermal impacts. An experimental case study compares our Chaotic Attractor Predictor (CAP) against previous prediction models constructed according to other statisti- cal methods. Our CAP is found to be accurate within an average error of 2% (or 7%) and the worst case error of 7% (or 20%) for the AMD Opteron processor (or for the Intel Nehalem processor), based on executing a set of SPEC CPU2006 benchmarks.
This work investigates operating-system assisted, hard- ware performance counter-based techniques... more This work investigates operating-system assisted, hard- ware performance counter-based techniques for thermal control in embedded systems running real-time applications. Such a technique schedules the processor workload in a way that reduces the thermal adverse impacts as much as possi- ble. It makes use of thread adjustment scheduling on multi- core processors to ensure active tasks observing their real- time deadlines with lowered performance overhead result- ing from fewer DTM events.
This paper proposes to develop a system-wide energy consumption model for servers by making use o... more This paper proposes to develop a system-wide energy consumption model for servers by making use of hardware performance counters and experimental measurements. We develop a real-time energy prediction model that relates server energy consumption to its overall thermal envelope. While previous studies have attempted system-wide modeling of server power consumption through subsystem models, our approach is different in that it uses a small set of tightly correlated parameters to create a model relating system energy input to subsystem energy consumption. We develop a linear regression model that relates processor power, bus activity, and system ambient temperatures into real-time predictions of the power consumption of long jobs and as result controlling their thermal impact. Using the HyperTransport bus model as a case study and through electrical measurements on example server subsystems, we develop a statistical model for estimating run-time power consumption. Our model is accurate within an error of four percent(4%) as verified using a set of common processor benchmarks.
Reliable remote measuring of flow meters for the petroleum gas industry is proposed in this work.... more Reliable remote measuring of flow meters for the petroleum gas industry is proposed in this work. The monitoring of flow rates and the total amount of the fluid flow is collected using a manual process. The main goal of this work is to implement a mechanism that avoids human error and achieves reliable, continuous, and accurate monitoring. We employed the NuFlo Measurement System Model MC-II Flow Analyzer to prototype our monitoring mechanism for measuring the liquid flow and a Crossbow Technology MICA2 mote and MDA300CA Data Acquisition Board to transmit collected data via a wireless sensor network (WSN). The flow analyzer generates a pulse signal whose frequency depends on the flow rate. The mote is used to count the number of pulses and send it to the host computer. An amplifier lets the mote detect the voltage level differences and overcome signal weakness. The host computer stores the data received from the mote into a PostgreSQL database for use in preparing Excel sheets and graphical displays in real time. The flow rate and the total flow amount collected by the host computer match those shown on analyzer. The design and implementation of our prototype serves as a proof of concept of how existing analog sensors used to monitor the flow rate and volume of the oil and water in petroleum production can be integrated with other devices in a WSN.
Abstract—Modern processors crudely manage thermal emergencies through Dynamic Thermal Management ... more Abstract—Modern processors crudely manage thermal emergencies through Dynamic Thermal Management (DTM), where the processor monitors the die temperature and dynamically adjusts the processor voltage and frequency (DVFS) to throttle down the processor when necessary. However, DVFS tends to yield marked degradation in both application performance and system reliability.
Abstract Reliable remote measuring of flow meters for the petroleum gas industry is proposed in t... more Abstract Reliable remote measuring of flow meters for the petroleum gas industry is proposed in this work. The monitoring of flow rates and the total amount of the fluid flow is collected using a manual process. The main goal of this work is to implement a mechanism that avoids human error and achieves reliable, continuous, and accurate monitoring.
Abstract This article proposes a runtime model that relates server energy consumption to its over... more Abstract This article proposes a runtime model that relates server energy consumption to its overall thermal envelope, using hardware performance counters and experimental measurements. While previous studies have attempted system-wide modeling of server power consumption through subsystem models, our approach is different in that it links system energy input to subsystem energy consumption based on a small set of tightly correlated parameters.
Abstract The discovery and management of energy resources, especially at locations in the Gulf of... more Abstract The discovery and management of energy resources, especially at locations in the Gulf of Mexico, requires an economic but technically enhanced infrastructure. Research teams from Louisiana State University, University of Louisiana at Lafayette, and Southern University Baton Rouge are engaged in a collaborative effort to create a ubiquitous computing and monitoring system (UCoMS) for the discovery and management of energy resources.
This paper proposes a chaotic time series model of server system- wide energy consumption to capt... more This paper proposes a chaotic time series model of server system- wide energy consumption to capture the dynamics present in ob- served sensor readings of underlying physical systems. Based on the chaotic model, we have developed a real-time predictor that es- timates actual server energy consumption according to its overall thermal envelope. This chaotic time series regression model relates processor power, bus activity, and system ambient temperatures for real-time prediction of power consumption during job execution to enable run-time control of their thermal impacts. An experimental case study compares our Chaotic Attractor Predictor (CAP) against previous prediction models constructed according to other statisti- cal methods. Our CAP is found to be accurate within an average error of 2% (or 7%) and the worst case error of 7% (or 20%) for the AMD Opteron processor (or for the Intel Nehalem processor), based on executing a set of SPEC CPU2006 benchmarks.
This work investigates operating-system assisted, hard- ware performance counter-based techniques... more This work investigates operating-system assisted, hard- ware performance counter-based techniques for thermal control in embedded systems running real-time applications. Such a technique schedules the processor workload in a way that reduces the thermal adverse impacts as much as possi- ble. It makes use of thread adjustment scheduling on multi- core processors to ensure active tasks observing their real- time deadlines with lowered performance overhead result- ing from fewer DTM events.
This paper proposes to develop a system-wide energy consumption model for servers by making use o... more This paper proposes to develop a system-wide energy consumption model for servers by making use of hardware performance counters and experimental measurements. We develop a real-time energy prediction model that relates server energy consumption to its overall thermal envelope. While previous studies have attempted system-wide modeling of server power consumption through subsystem models, our approach is different in that it uses a small set of tightly correlated parameters to create a model relating system energy input to subsystem energy consumption. We develop a linear regression model that relates processor power, bus activity, and system ambient temperatures into real-time predictions of the power consumption of long jobs and as result controlling their thermal impact. Using the HyperTransport bus model as a case study and through electrical measurements on example server subsystems, we develop a statistical model for estimating run-time power consumption. Our model is accurate within an error of four percent(4%) as verified using a set of common processor benchmarks.
Reliable remote measuring of flow meters for the petroleum gas industry is proposed in this work.... more Reliable remote measuring of flow meters for the petroleum gas industry is proposed in this work. The monitoring of flow rates and the total amount of the fluid flow is collected using a manual process. The main goal of this work is to implement a mechanism that avoids human error and achieves reliable, continuous, and accurate monitoring. We employed the NuFlo Measurement System Model MC-II Flow Analyzer to prototype our monitoring mechanism for measuring the liquid flow and a Crossbow Technology MICA2 mote and MDA300CA Data Acquisition Board to transmit collected data via a wireless sensor network (WSN). The flow analyzer generates a pulse signal whose frequency depends on the flow rate. The mote is used to count the number of pulses and send it to the host computer. An amplifier lets the mote detect the voltage level differences and overcome signal weakness. The host computer stores the data received from the mote into a PostgreSQL database for use in preparing Excel sheets and graphical displays in real time. The flow rate and the total flow amount collected by the host computer match those shown on analyzer. The design and implementation of our prototype serves as a proof of concept of how existing analog sensors used to monitor the flow rate and volume of the oil and water in petroleum production can be integrated with other devices in a WSN.
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Papers by Adam Lewis