The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform
Darrell Jan - One of the best experts on this subject based on the ideXlab platform.
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integrated atmosphere resource recovery and environmental monitoring technology demonstration for deep Space Exploration
42nd International Conference on Environmental Systems, 2012Co-Authors: Jay L Perry, Morgan B Abney, James C Knox, Keith J Parrish, Monserrate C Roman, Darrell JanAbstract:Exploring the frontiers of deep Space presents numerous technological challenges associated with safely transporting a crew to and from destinations of scientific interest. Living and working on that frontier requires a highly robust life support system based on proven process technologies. The International Space Station (ISS), including its environmental control and life support (ECLS) system, is the platform from which humanity’s deep Space Exploration missions begin. The atmosphere revitalization (AR) subsystem within the ECLS system and the environmental monitoring (EM) technical architecture aboard the ISS are evaluated as the starting basis for a developmental effort being conducted by the National Aeronautics and Space Administration (NASA) via the Advanced Exploration Systems (AES) Atmosphere Resource Recovery and Environmental Monitoring (ARREM) Project. An evolutionary approach is used by the ARREM project to address the strengths and weaknesses of the ISS AR subsystem and EM equipment, core process technologies, and operational approaches to reduce developmental risk, improve functional reliability, and lower lifecycle costs of an architecture suitable for use for crewed deep Space Exploration missions. An ISS-derived subsystem design architecture that incorporates core process technology upgrades or replacements will be matured through a series of integrated tests and architectural trade studies that encompass deep Space Exploration mission requirements and constraints.
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integrated atmosphere resource recovery and environmental monitoring technology demonstration for deep Space Exploration
42nd International Conference on Environmental Systems, 2012Co-Authors: Jay L Perry, Morgan B Abney, James C Knox, Keith J Parrish, Monserrate C Roman, Darrell JanAbstract:Exploring the frontiers of deep Space continues to be defined by the technological challenges presented by safely transporting a crew to and from destinations of scientific interest. Living and working on that frontier requires highly reliable and efficient life support systems that employ robust, proven process technologies. The International Space Station (ISS), including its environmental control and life support (ECLS) system, is the platform from which humanity's deep Space Exploration missions begin. The ISS ECLS system Atmosphere Revitalization (AR) subsystem and environmental monitoring (EM) technical architecture aboard the ISS is evaluated as the starting basis for a developmental effort being conducted by the National Aeronautics and Space Administration (NASA) via the Advanced Exploration Systems (AES) Atmosphere Resource Recovery and Environmental Monitoring (ARREM) Project.. An evolutionary approach is employed by the ARREM project to address the strengths and weaknesses of the ISS AR subsystem and EM equipment, core technologies, and operational approaches to reduce developmental risk, improve functional reliability, and lower lifecycle costs of an ISS-derived subsystem architecture suitable for use for crewed deep Space Exploration missions. The most promising technical approaches to an ISS-derived subsystem design architecture that incorporates promising core process technology upgrades will be matured through a series of integrated tests and architectural trade studies encompassing expected Exploration mission requirements and constraints.
Davide Bertozzi - One of the best experts on this subject based on the ideXlab platform.
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ssdexplorer a virtual platform for performance reliability oriented fine grained design Space Exploration of solid state drives
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2015Co-Authors: Lorenzo Zuolo, Cristian Zambelli, Rino Micheloni, Marco Indaco, Stefano Di Carlo, Paolo Prinetto, Davide Bertozzi, Patrizia D'olivoAbstract:Currently available electronic design automation tools for design Space Exploration of solid state drives (SSDs) are not able to assess: 1) the device architecture inefficiencies; 2) architecture overdesign for a target performance; and 3) performance degradation caused by the disk usage. These tools feature either an overly high abstraction modeling strategy or lack the required flexibility to perform design Exploration. To overcome these problems, this paper proposes SSDExplorer, a tool for fine-grained yet reasonably fast design Space Exploration of different SSD architectures highlighting possible bottlenecks. To prove its accuracy SSDExplorer has been validated with two real SSDs. SSDExplorer efficiency has been assessed by evaluating the impact of the NAND flash read retry algorithm impact on the SSD performance as a function of its internal architecture.
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ssdexplorer a virtual platform for fine grained design Space Exploration of solid state drives
Design Automation and Test in Europe, 2014Co-Authors: Lorenzo Zuolo, Cristian Zambelli, Rino Micheloni, Salvatore Galfano, Marco Indaco, Stefano Di Carlo, Paolo Prinetto, Patrizia D'olivo, Davide BertozziAbstract:Solid State Drives (SSDs) are gaining particular momentum in various frameworks such as multimedia, large data centers and cloud environments. Unfortunately, efficient CAD tools for SSD design Space Exploration able to assess the optimization of the device microarchitecture w.r.t. the target performance are still missing. This paper tries to close this gap by proposing SSDExplorer, a tool for fine-grained and fast design Space Exploration of SSD devices. SSDExplorer provides unprecedented insights into the architecture behavior and subcomponent interaction efficiency, while avoiding the need for the actual implementation of an FTL or of key hardware components. This is achieved by the introduction of suitable abstractions of the different components. This is confirmed by the thorough validation of SSDExplorer against a commercial SSD device.
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ssdexplorer a virtual platform for fine grained design Space Exploration of solid state drives
Design Automation and Test in Europe, 2014Co-Authors: Lorenzo Zuolo, Cristian Zambelli, Rino Micheloni, Salvatore Galfano, Marco Indaco, Stefano Di Carlo, Paolo Prinetto, Patrizia D'olivo, Davide BertozziAbstract:Solid State Drives (SSDs) are gaining particular momentum in various frameworks such as multimedia, large data centers and cloud environments. Unfortunately, efficient CAD tools for SSD design Space Exploration able to assess the optimization of the device microarchitecture w.r.t. the target performance are still missing. This paper tries to close this gap by proposing SSDExplorer, a tool for fine-grained and fast design Space Exploration of SSD devices. SSDExplorer provides unprecedented insights into the architecture behavior and subcomponent interaction efficiency, while avoiding the need for the actual implementation of an FTL or of key hardware components. This is achieved by the introduction of suitable abstractions of the different components. This is confirmed by the thorough validation of SSDExplorer against a commercial SSD device.
Jay L Perry - One of the best experts on this subject based on the ideXlab platform.
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integrated atmosphere resource recovery and environmental monitoring technology demonstration for deep Space Exploration
42nd International Conference on Environmental Systems, 2012Co-Authors: Jay L Perry, Morgan B Abney, James C Knox, Keith J Parrish, Monserrate C Roman, Darrell JanAbstract:Exploring the frontiers of deep Space presents numerous technological challenges associated with safely transporting a crew to and from destinations of scientific interest. Living and working on that frontier requires a highly robust life support system based on proven process technologies. The International Space Station (ISS), including its environmental control and life support (ECLS) system, is the platform from which humanity’s deep Space Exploration missions begin. The atmosphere revitalization (AR) subsystem within the ECLS system and the environmental monitoring (EM) technical architecture aboard the ISS are evaluated as the starting basis for a developmental effort being conducted by the National Aeronautics and Space Administration (NASA) via the Advanced Exploration Systems (AES) Atmosphere Resource Recovery and Environmental Monitoring (ARREM) Project. An evolutionary approach is used by the ARREM project to address the strengths and weaknesses of the ISS AR subsystem and EM equipment, core process technologies, and operational approaches to reduce developmental risk, improve functional reliability, and lower lifecycle costs of an architecture suitable for use for crewed deep Space Exploration missions. An ISS-derived subsystem design architecture that incorporates core process technology upgrades or replacements will be matured through a series of integrated tests and architectural trade studies that encompass deep Space Exploration mission requirements and constraints.
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integrated atmosphere resource recovery and environmental monitoring technology demonstration for deep Space Exploration
42nd International Conference on Environmental Systems, 2012Co-Authors: Jay L Perry, Morgan B Abney, James C Knox, Keith J Parrish, Monserrate C Roman, Darrell JanAbstract:Exploring the frontiers of deep Space continues to be defined by the technological challenges presented by safely transporting a crew to and from destinations of scientific interest. Living and working on that frontier requires highly reliable and efficient life support systems that employ robust, proven process technologies. The International Space Station (ISS), including its environmental control and life support (ECLS) system, is the platform from which humanity's deep Space Exploration missions begin. The ISS ECLS system Atmosphere Revitalization (AR) subsystem and environmental monitoring (EM) technical architecture aboard the ISS is evaluated as the starting basis for a developmental effort being conducted by the National Aeronautics and Space Administration (NASA) via the Advanced Exploration Systems (AES) Atmosphere Resource Recovery and Environmental Monitoring (ARREM) Project.. An evolutionary approach is employed by the ARREM project to address the strengths and weaknesses of the ISS AR subsystem and EM equipment, core technologies, and operational approaches to reduce developmental risk, improve functional reliability, and lower lifecycle costs of an ISS-derived subsystem architecture suitable for use for crewed deep Space Exploration missions. The most promising technical approaches to an ISS-derived subsystem design architecture that incorporates promising core process technology upgrades will be matured through a series of integrated tests and architectural trade studies encompassing expected Exploration mission requirements and constraints.
Jurgen Teich - One of the best experts on this subject based on the ideXlab platform.
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efficient symbolic multi objective design Space Exploration
Asia and South Pacific Design Automation Conference, 2008Co-Authors: Martin Lukasiewycz, Michael Glaß, Christian Haubelt, Jurgen TeichAbstract:Nowadays many design Space Exploration tools are based on Multi-Objective Evolutionary Algorithms (MOEAs). Beside the advantages of MOEAs, there is one important drawback as MOEAs might fail in design Spaces containing only a few feasible solutions or as they are often afflicted with premature convergence, i.e., the same design points are revisited again and again. Exact methods, especially Pseudo Boolean solvers (PB solvers) seem to be a solution. However, as typical design Spaces are multi-objective, there is a need for multi-objective PB solvers. In this paper, we will formalize the problem of design Space Exploration as multi-objective 0--1 ILP. We will propose (1) a heuristic approach based on PB solvers and (2) a complete multi-objective PB solver based on a backtracking algorithm that incorporates the non-dominance relation from multi-objective optimization and is restricted to linear objective functions. First results from applying our novel multi-objective PB solver to synthetic problems will show its effectiveness in small sized design Spaces as well as in large design Spaces only containing a few feasible solutions. For non-linear and large problems, the proposed heuristic approach is outperforming common MOEA approaches. Finally, a real world example from the automotive area will emphasize the efficiency of the proposed algorithms.
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accelerating design Space Exploration using pareto front arithmetics
Asia and South Pacific Design Automation Conference, 2003Co-Authors: Christian Haubelt, Jurgen TeichAbstract:In this paper, we propose an approach for the synthesis of heterogeneous (embedded) systems, while exploiting a hierarchical problem structure. Particular to our approach is that we explore the set of so-called Pareto-optimal solutions, i.e., optimizing multiple objectives simultaneously. Since system complexity grows steadily leading to giant search Spaces which demand for new strategies in design Space Exploration, we propose Pareto-Front Arithmetics (PFA) using results of subsystems to construct implementations of the top-level system. This way, we are able to reduce the Exploration time dramatically. An example of an MPEG4 coder is used to show the benefit of this approach in real-life applications.
David I. August - One of the best experts on this subject based on the ideXlab platform.
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compiler optimization Space Exploration
Symposium on Code Generation and Optimization, 2003Co-Authors: Spyridon Triantafyllis, Manish Vachharajani, Neil Vachharajani, David I. AugustAbstract:To meet the demands of modern architectures, optimizing compilers must incorporate an ever larger number of increasingly complex transformation algorithms. Since code transformations may often degrade performance or interfere with subsequent transformations, compilers employ predictive heuristics to guide optimizations by predicting their effects a priori. Unfortunately, the unpredictability of optimization interaction and the irregularity of today's wide-issue machines severely limit the accuracy of these heuristics. As a result, compiler writers may temper high variance optimization with overly conservative heuristics or may exclude these optimizations entirely. While this process results in a compiler capable of generating good average code quality across the target benchmark set, it is at the cost of missed optimization opportunities in individual code segments.To replace predictive heuristics, researchers have proposed compilers which explore many optimization options, selecting the best one a posteriori. Unfortunately, these existing iterative compilation techniques are not practical for reasons of compile time and applicability. In this paper, we present the Optimization-Space Exploration (OSE) compiler organization, the first practical iterative compilation strategy applicable to optimizations in general-purpose compilers. Instead of replacing predictive heuristics, OSE uses the compiler writer's knowledge encoded in the heuristics to select a small number of promising optimization alternatives for a given code segment. Compile time is limited by evaluating only these alternatives for hot code segments using a general compiletime performance estimator. An OSE-enhanced version of lntel's highly-tuned, aggressively optimizing production compiler for IA-64 yields a significant performance improvement, more than 20% in some cases, on Itanium for SPEC codes.
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compiler optimization Space Exploration
Symposium on Code Generation and Optimization, 2003Co-Authors: Spyridon Triantafyllis, Manish Vachharajani, Neil Vachharajani, David I. AugustAbstract:To meet the demands of modern architectures, optimizing compilers must incorporate an ever larger number of increasingly complex transformation algorithms. Since code transformations may often degrade performance or interfere with subsequent transformations, compilers employ predictive heuristics to guide optimizations by predicting their effects a priori. Unfortunately, the unpredictability of optimization interaction and the irregularity of today's wide-issue machines severely limit the accuracy of these heuristics. As a result, compiler writers may temper high variance optimization with overly conservative heuristics or may exclude these optimizations entirely. While this process results in a compiler capable of generating good average code quality across the target benchmark set, it is at the cost of missed optimization opportunities in individual code segments.To replace predictive heuristics, researchers have proposed compilers which explore many optimization options, selecting the best one a posteriori. Unfortunately, these existing iterative compilation techniques are not practical for reasons of compile time and applicability. In this paper, we present the Optimization-Space Exploration (OSE) compiler organization, the first practical iterative compilation strategy applicable to optimizations in general-purpose compilers. Instead of replacing predictive heuristics, OSE uses the compiler writer's knowledge encoded in the heuristics to select a small number of promising optimization alternatives for a given code segment. Compile time is limited by evaluating only these alternatives for hot code segments using a general compiletime performance estimator. An OSE-enhanced version of lntel's highly-tuned, aggressively optimizing production compiler for IA-64 yields a significant performance improvement, more than 20% in some cases, on Itanium for SPEC codes.
