Memory Systems

Is your memory hierarchy stopping your microprocessor from performing at the high level it should be? Memory Systems: Cache, DRAM, Disk shows you how to resolve this problem. The book tells you everything you need to know about the logical design and operation, physical design and operation, performance characteristics and resulting design trade-offs, and the energy consumption of modern memory hierarchies. You learn how to to tackle the challenging optimization problems that result from the side-effects that can appear at any point in the entire hierarchy.As a result you will be able to design and emulate the entire memory hierarchy. Understand all levels of the system hierarchy -Xcache, DRAM, and disk. Evaluate the system-level effects of all design choices. Model performance and energy consumption for each component in the memory hierarchy.

Assembled by the prominent psychologists Daniel Schacter and Endel Tulving, the contributions in "Memory Systems 1994" focus on the nature and number of memory systems in humans and animals. Together they present ideas from cognitive psychology, neuropsychology, and neuroscience in a review of intriguing experimental outcomes at the cutting edge of this domain, grappling, often passionately, with the behavioral and neuroanatomical composition of memory systems and subsystems. Chapters are revised versions of contributions that appeared in a special issue of the Journal of Cognitive Neuroscience. This book includes an integrated discussion of and cross-commentary on the earlier contributions. "A Bradford Book"

The Evolution of Memory Systems sets out a bold and exciting new theory about memory. It proposes that several memory systems arose during evolution and that they did so for the same general reason: to transcend problems and exploit opportunities encountered by specific ancestors at particular times and places in the distant past.

The brain ... There is no other part of the human anatomy that is so intriguing. How does it develop and function and why does it sometimes, tragically, degenerate? The answers are complex. In Discovering the Brain, science writer Sandra Ackerman cuts through the complexity to bring this vital topic to the public. The 1990s were declared the "Decade of the Brain" by former President Bush, and the neuroscience community responded with a host of new investigations and conferences. Discovering the Brain is based on the Institute of Medicine conference, Decade of the Brain: Frontiers in Neuroscience and Brain Research. Discovering the Brain is a "field guide" to the brainâ€"an easy-to-read discussion of the brain's physical structure and where functions such as language and music appreciation lie. Ackerman examines: How electrical and chemical signals are conveyed in the brain. The mechanisms by which we see, hear, think, and pay attentionâ€"and how a "gut feeling" actually originates in the brain. Learning and memory retention, including parallels to computer memory and what they might tell us about our own mental capacity. Development of the brain throughout the life span, with a look at the aging brain. Ackerman provides an enlightening chapter on the connection between the brain's physical condition and various mental disorders and notes what progress can realistically be made toward the prevention and treatment of stroke and other ailments. Finally, she explores the potential for major advances during the "Decade of the Brain," with a look at medical imaging techniquesâ€"what various technologies can and cannot tell usâ€"and how the public and private sectors can contribute to continued advances in neuroscience. This highly readable volume will provide the public and policymakersâ€"and many scientists as wellâ€"with a helpful guide to understanding the many discoveries that are sure to be announced throughout the "Decade of the Brain."

The State of Memory Technology Over the past decade there has been rapid growth in the speed of micropro cessors. CPU speeds are approximately doubling every eighteen months, while main memory speed doubles about every ten years. The International Tech nology Roadmap for Semiconductors (ITRS) study suggests that memory will remain on its current growth path. The ITRS short-and long-term targets indicate continued scaling improvements at about the current rate by 2016. This translates to bit densities increasing at two times every two years until the introduction of 8 gigabit dynamic random access memory (DRAM) chips, after which densities will increase four times every five years. A similar growth pattern is forecast for other high-density chip areas and high-performance logic (e.g., microprocessors and application specific inte grated circuits (ASICs)). In the future, molecular devices, 64 gigabit DRAMs and 28 GHz clock signals are targeted. Although densities continue to grow, we still do not see significant advances that will improve memory speed. These trends have created a problem that has been labeled the Memory Wall or Memory Gap.

Memory Systems and Pipelined Processors

We are pleased to present this collection of papers from the Second Workshop on Intelligent Memory Systems. Increasing die densities and inter chip communication costs continue to fuel interest in intelligent memory systems. Since the First Workshop on Mixing Logic and DRAM in 1997, technologies and systems for computation in memory have developed quickly. The focus of this workshop was to bring together researchers from academia and industry to discuss recent progress and future goals. The program committee selected 8 papers and 6 poster session abstracts from 29 submissions for inclusion in the workshop. Four to five members of the program committee reviewed each submission and their reviews were used to numerically rank them and guide the selection process. We believe that the resulting program is of the highest quality and interest possible. The selected papers cover a wide range of research topics such as circuit technology, processor and memory system architecture, compilers, operating systems, and applications. They also present a mix of mature projects, work in progress, and new research ideas. The workshop also included two invited talks. Dr. Subramanian Iyer (IBM Microelectronics) provided an overview of embedded memory technology and its potential. Dr. Mark Snir (IBM Research) presented the Blue Gene, an aggressive supercomputer system based on intelligent memory technology.

Drug addiction may be viewed as a form of learning during which strong associations linking actions to drug-seeking are expressed as persistent stimulus–response habits, thereby maintaining a vulnerability to relapse. Disrupting cue–drug memory could be an efficient strategy to reduce the strength of cues in motivating drug-taking behavior. Upon reactivation, these memories undergo a reconsolidation process that can be blocked pharmacologically, providing an opportunity to prevent the powerful control of drug cues on behavior. This conceptually elegant approach still calls for more experimental data. However, an increasing body of evidence suggests that drug taking not only accelerates habit forming, but has long-lasting effects on interactions between memory systems eventually leading to a functional imbalance. The dorsal part of the striatum plays a critical role in habit/procedural learning, whereas the hippocampal memory system encodes relationships between events and their later flexible use. Both humans and rodents studies support the view that the hippocampus and the dorsal striatum interact in either a cooperative or competitive manner during learning, the prefrontal cortex being involved in the selection of an appropriate learning strategy. Chronic drug consumption biases normal interactions between these memory systems. For instance, drug-experienced rodents tend to use preferentially striatum-dependent learning strategies in navigational tasks. These persistent effects seem to occur at cellular, neurophysiological and behavioral levels to promote specific, striatal-dependent forms of learning, to the detriment of spatial/declarative, hippocampal-dependent and more flexible types of memory. Whether cue sensitive and response learners, in contrast to spatial learners, could be prone to drug addiction is an intriguing hypothesis which clearly deserves to be further explored. A loss of flexibility may be uncovered also by imposing changing rules on the subject, such as requiring an attentional shift between different perceptual features of a complex stimulus, as in the attentional set shifting task which was recently adapted to rodents. Working memory is at risk during transition phases, although it remains to be determined whether withdrawal-induced alterations are observed also during protracted abstinence. Drug-induced cognitive biases thus lead to cognitive rigidity which could play a critical, yet overlooked role in different phases of addiction (acquisition, extinction/withdrawal and relapse). They are also likely to preclude the clinical efficiency of treatments. Therefore, the aim of this research topic is to provide an overview of the current work investigating the long-term impact of drug use on learning and memory processes, how multiple memory systems modulate drug-seeking behavior, as well as how drug-induced cognitive biases could contribute to the persistence of addictive behaviors.

"Simple instructions for creating a wide variety of graphic cuing systems are provided, with numerous examples of useful content and format. Additional tools include forms and templates to photocopy, a list of sources for materials, and instructions and patterns for creating portable, wearable memory aids. Speech-language pathologists, occupational and physical therapists, activity directors, direct care staff, and family members interacting with adults with memory impairments will welcome this practical and life-enhancing resource."--BOOK JACKET.

Memory is a universal function of organized matter. What is the mathematics of memory? How does memory affect the space-time behaviour of spatially extended systems? Does memory increase complexity? This book provides answers to these questions. It focuses on the study of spatially extended systems, i.e., cellular automata and other related discrete complex systems. Thus, arrays of locally connected finite state machines, or cells, update their states simultaneously, in discrete time, by the same transition rule. The classical dynamics in these systems is Markovian: only the actual configuration is taken into account to generate the next one. Generalizing the conventional view on spatially extended discrete dynamical systems evolution by allowing cells (or nodes) to be featured by some trait state computed as a function of its own previous state-values, the transition maps of the classical systems are kept unaltered, so that the effect of memory can be easily traced. The book demonstrates that discrete dynamical systems with memory are not only priceless tools for modeling natural phenomena but unique mathematical and aesthetic objects.