02290nam a2200265 a 4500 vtls000081345 KUKTEM 20251125100058.0 140617t2014 nyua f 001 0 eng d 9781461477976 (hbk.) 201506181412 aida 201406171400 ezzatul UMP TK7885 .P38 2014 Paul, Somnath Computing with memory for energy-efficient robust systems / Somnath Paul, Swarup Bhunia New York : Springer, 2014 xiii, 210 p. : ill. (some col.) ; 22 cm. Includes bibliographical references This book analyzes energy and reliability as major challenges faced by designers of computing frameworks in the nanometer technology regime. The authors describe the existing solutions to address these challenges and then reveal a new reconfigurable computing platform, which leverages high-density nanoscale memory for both data storage and computation to maximize the energy-efficiency and reliability. The energy and reliability benefits of this new paradigm are illustrated and the design challenges are discussed. Various hardware and software aspects of this exciting computing paradigm are described, particularly with respect to hardware-software co-designed frameworks, where the hardware unit can be reconfigured to mimic diverse application behavior. Finally, the energy-efficiency of the paradigm described is compared with other, well-known reconfigurable computing platforms. Introduces new paradigm for hardware reconfigurable frameworks, which leverages dense memory array as a malleable resource, which can be used for information storage as well as computation; Merges spatial and temporal computing to minimize interconnect overhead and achieve better scalability compared to state-of-the-art reconfigurable computing platforms; Enables efficient mapping of diverse data-intensive applications from domains of signal processing, multimedia and security applications Computer engineering Computers Energy consumption Nanoelectromechanical systems Bhunia, Swarup 0 0 0 0 20000 20000 2019-09-04 411.12 0 TK7885 .P38 2014 0000097855 2019-09-04 00:00:00 1 411.12 2019-09-04 OPEN VIRTUA40 77329 77335 VTLSSORT0080*0200*0400*0900*1000*2450*2600*3000*5040*5200*6500*6501*6502*7000*9992