Akash Kumar

Modern multimedia systems are becoming increasingly multiprocessor and heterogeneous to match the high performance and low power demands placed on them by the large number of applications. The concurrent execution of these applications causes interference and unpredictability in the performance of these systems. In Multimedia Multiprocessor Systems, an analysis mechanism is presented to accurately predict the performance of multiple applications executing concurrently. With high consumer demand the time-to-market has become significantly lower. To cope with the complexity in designing such systems, an automated design-flow is needed that can generate systems from a high-level architectural description such that they are not error-prone and consume less time. Such a design methodology is presented for multiple use-cases -- combinations of active applications. A resource manager is also presented to manage the various resources in the system, and to achieve the goals of performance prediction, admission control and budget enforcement.

This book addresses the challenges associated with efficient Mixed-Criticality (MC) system design. We focus on application analysis through execution time analysis and task scheduling analysis in order to execute more low-criticality tasks in the system, i.e., improving the Quality-of-Service (QoS), while guaranteeing the correct execution of high-criticality tasks. Further, this book addresses the challenge of enhancing QoS using parallelism in multi-processor hardware platforms.

Modern multimedia systems are becoming increasingly multiprocessor and heterogeneous to match the high performance and low power demands placed on them by the large number of applications. The concurrent execution of these applications causes interference and unpredictability in the performance of these systems. In Multimedia Multiprocessor Systems, an analysis mechanism is presented to accurately predict the performance of multiple applications executing concurrently. With high consumer demand the time-to-market has become significantly lower. To cope with the complexity in designing such systems, an automated design-flow is needed that can generate systems from a high-level architectural description such that they are not error-prone and consume less time. Such a design methodology is presented for multiple use-cases -- combinations of active applications. A resource manager is also presented to manage the various resources in the system, and to achieve the goals of performance prediction, admission control and budget enforcement.

We focus on application analysis through execution time analysis and task scheduling analysis in order to execute more low-criticality tasks in the system, i.e., improving the Quality-of-Service (QoS), while guaranteeing the correct execution of high-criticality tasks.

This book is a single-source solution for anyone who is interested in exploring emerging reconfigurable nanotechnology at the circuit level. It lays down a solid foundation for circuits based on this technology having considered both manual as well as automated design flows. The authors discuss the entire design flow, consisting of both logic and physical synthesis for reconfigurable nanotechnology-based circuits. The authors describe how transistor reconfigurable properties can be exploited at the logic level to have a more efficient circuit design flow, as compared to conventional design flows suited for CMOS.Further,the book provides insights into hardware security features that can be intrinsically developed using the runtime reconfigurable features of this nanotechnology.

This book presents various novel architectures for FPGA-optimized accurate and approximate operators, their detailed accuracy and performance analysis, various techniques to model the behavior of approximate operators, and thorough application-level analysis to evaluate the impact of approximations on the final output quality and performance metrics. As multiplication is one of the most commonly used and computationally expensive operations in various error-resilient applications such as digital signal and image processing and machine learning algorithms, this book particularly focuses on this operation. The book starts by elaborating on the various sources of error resilience and opportunities available for approximations on various layers of the computation stack. It then provides a detailed description of the state-of-the-art approximate computing-related works and highlights their limitations.

This book is a single-source solution for anyone who is interested in exploring emerging reconfigurable nanotechnology at the circuit level. It lays down a solid foundation for circuits based on this technology having considered both manual as well as automated design flows. The authors discuss the entire design flow, consisting of both logic and physical synthesis for reconfigurable nanotechnology-based circuits. The authors describe how transistor reconfigurable properties can be exploited at the logic level to have a more efficient circuit design flow, as compared to conventional design flows suited for CMOS. Further, the book provides insights into hardware security features that can be intrinsically developed using the runtime reconfigurable features of this nanotechnology.

Dieses Buch beschreibt eine neue, grobkörnige rekonfigurierbare Architektur (CGRA), genannt Blocks, und stellt sie in den Kontext von Computerarchitekturen und insbesondere von anderen CGRAs. Das Buch beginnt mit einer ausführlichen Bewertung historischer und bestehender CGRAs und deren Stärken und Schwächen. Dies führt auch zu einem besseren Verständnis und einer neuen Definition dessen, was CGRAs von anderen Architekturansätzen unterscheidet. Die Autoren stellen Blocks als einzigartig vor, da es über separate programmierbare Steuer- und Datenpfade verfügt, so dass leichtgewichtige Befehlsdekodiereinheiten über eine statisch konfigurierte Verbindung beliebig mit einer oder mehreren Funktionseinheiten (FUs) verbunden werden können. In der Diskussion wird erläutert, wie Architekturen modelliert werden können, was zu einem Flächen- und Energiemodell für Blöcke führt. Die Genauigkeit dieses Modells wird anhand vollständig implementierter Architekturen bewertet, wobei sich zeigt, dass die Fehlerspanne sehr akzeptabel ist, obwohl es um drei Größenordnungen schneller ist als die Synthese. Das Buch schließt mit einer Fallstudie zu einem echten System-on-Chip, einschließlich einer RISC-Architektur, der Blocks CGRA und Peripheriegeräten.

This book presents various novel architectures for FPGA-optimized accurate and approximate operators, their detailed accuracy and performance analysis, various techniques to model the behavior of approximate operators, and thorough application-level analysis to evaluate the impact of approximations on the final output quality and performance metrics. As multiplication is one of the most commonly used and computationally expensive operations in various error-resilient applications such as digital signal and image processing and machine learning algorithms, this book particularly focuses on this operation. The book starts by elaborating on the various sources of error resilience and opportunities available for approximations on various layers of the computation stack. It then provides a detailed description of the state-of-the-art approximate computing-related works and highlights their limitations.

This book describes a new, coarse-grained reconfigurable architecture (CGRA), called Blocks, and puts it in the context of computer architectures, and in particular of other CGRAs. The book starts with an extensive evaluation of historic and existing CGRAs and their strengths and weaknesses. This also leads to a better understanding and new definition of what distinguishes CGRAs from other architectural approaches. The authors introduce Blocks as unique due to its separate programmable control and data paths, allowing light-weight instruction decode units to be arbitrarily connected to one or more functional units (FUs) over a statically configured interconnect. The discussion includes an explanation of how to model architectures, resulting in an area and energy model for Blocks. The accuracy of this model is evaluated against fully implemented architectures, showing that although it is three orders of magnitude faster than synthesis the error margin is very acceptable. Thebook concludes with a case study on a real System-on-Chip, including a RISC architecture, the Blocks CGRA and peripherals.

This book describes a new, coarse-grained reconfigurable architecture (CGRA), called Blocks, and puts it in the context of computer architectures, and in particular of other CGRAs. The book starts with an extensive evaluation of historic and existing CGRAs and their strengths and weaknesses. This also leads to a better understanding and new definition of what distinguishes CGRAs from other architectural approaches. The authors introduce Blocks as unique due to its separate programmable control and data paths, allowing light-weight instruction decode units to be arbitrarily connected to one or more functional units (FUs) over a statically configured interconnect. The discussion includes an explanation of how to model architectures, resulting in an area and energy model for Blocks. The accuracy of this model is evaluated against fully implemented architectures, showing that although it is three orders of magnitude faster than synthesis the error margin is very acceptable. Thebook concludes with a case study on a real System-on-Chip, including a RISC architecture, the Blocks CGRA and peripherals.

This is an anthology of poems and articles based on our lives. One can find various types of contents starting from the poems based on our life to the articles related to real-life issues in this anthology. If you like poems and articles to read, then this is a combination of poems as well as articles.

This book deals with various short poems written by the author which is basically related to normal as well as love life.

This book discusses analysis, design and optimization techniques for streaming multiprocessor systems, while satisfying a given area, performance, and energy budget. The authors describe design flows for both application-specific and general purpose streaming systems. Coverage also includes the use of machine learning for thermal optimization at run-time, when an application is being executed. The design flow described in this book extends to thermal and energy optimization with multiple applications running sequentially and concurrently.

This book discusses analysis, design and optimization techniques for streaming multiprocessor systems, while satisfying a given area, performance, and energy budget. The authors describe design flows for both application-specific and general purpose streaming systems. Coverage also includes the use of machine learning for thermal optimization at run-time, when an application is being executed. The design flow described in this book extends to thermal and energy optimization with multiple applications running sequentially and concurrently.