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Computer Architecture: A Quantitative Approach
This best-selling title, considered for over a decade to be essential reading for every serious student and practitioner of computer design, has been updated throughout to address the most important…
A view of cloud computing
Clearing the clouds away from the true potential and obstacles posed by this computing capability.
Above the Clouds: A Berkeley View of Cloud Computing
This work focuses on SaaS Providers (Cloud Users) and Cloud Providers, which have received less attention than SAAS Users, and uses the term Private Cloud to refer to internal datacenters of a business or other organization, not made available to the general public.
A case for redundant arrays of inexpensive disks (RAID)
Five levels of RAIDs are introduced, giving their relative cost/performance, and a comparison to an IBM 3380 and a Fujitsu Super Eagle is compared.
The Landscape of Parallel Computing Research: A View from Berkeley
The parallel landscape is frame with seven questions, and the following are recommended to explore the design space rapidly: • The overarching goal should be to make it easy to write programs that execute efficiently on highly parallel computing systems • The target should be 1000s of cores per chip, as these chips are built from processing elements that are the most efficient in MIPS (Million Instructions per Second) per watt, MIPS per area of silicon, and MIPS each development dollar.
LogP: towards a realistic model of parallel computation
A new parallel machine model, called LogP, is offered that reflects the critical technology trends underlying parallel computers and is intended to serve as a basis for developing fast, portable parallel algorithms and to offer guidelines to machine designers.
RAID: high-performance, reliable secondary storage
A comprehensive overview of disk array technology and implementation topics such as refining the basic RAID levels to improve performance and designing algorithms to maintain data consistency are discussed.
Detecting large-scale system problems by mining console logs
This work first parse console logs by combining source code analysis with information retrieval to create composite features, and then analyzes these features using machine learning to detect operational problems to automatically detect system runtime problems.
The RISC-V Instruction Set Manual
This draft specification may change before being accepted as standard by the RISC-V Foundation, and it remains possible that implementations made to this draft specification will not conform to the future standard.
Computer Architecture - A Quantitative Approach, 5th Edition
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