Research Papers On Computer Architecture

Memory: Memory access times are not speeding up as quickly as CPU times, which in effect means that memory access is “slower”, or rather, takes more CPU cycles.Interest in technology and algorithms to help speed up memory access will not go away anytime soon, in my opinion.

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It is a direct evolution of the Monash multiprocessing kernel, developed for the Monash multiprocessor system in 1987, and a major research accomplishment by a long running research group founded and led by the late Professor Chris Wallace.

Previous Wal NUT related projects included the addition of a stdio libraries, a compiler port, a network protocol stack design, a shell design and other miscellaneous topics.

Power: The proliferation of mobile devices as well as the power wall necessitate a need for low-power solutions.

The need for saving power will not go away, so there should be ample interest and opportunities in this area.

General Scope “Heterogeneity in Architectures and Systems – From Embedded to HPC” was the specific focus of the International Conference on Architecture of Computing Systems (ARCS 2016).

This leitmotif reflected the ongoing progress in semiconductor technology that allows for building fascinating, complex computing systems, including multiple (heterogeneous) microprocessors, large on-chip memory hierarchies, advanced interconnection networks, and peripherals.Striking ones to me are: Deep Learning: Based on some of the papers I’ve skimmed, this is a very young research area that isn’t yet close to catching up to the state-of-the-art with regards to deep learning, which means there is plenty of low-hanging fruit.The papers accepted to ISCA 2016 generally focus on accelerators for convolutional neural networks.Here are some other topics that I recall reading about in 2013–2014 but may have gone out of fashion since then: Heterogeneous Architectures: We are at the point where we are unable to power all of the transistors we have on chip.Ways around this have generally involved heterogenous architectures, where you have multiple distinct computation units that are optimized in terms of performance and power for specific tasks. I saw some abstracts in this area in the ISCA table of contents, so it seems this is still a relevant field, albeit a more mature one that probably has less low-hanging fruit than other disciplines.Still, it won’t stop researches from trying, and I’m pretty sure people are still publishing papers in this area.Unfortunately, a lot of topics that are fundamental to understanding computer architecture are basically dead at this point: Branch Prediction: This field is dead. Single-core optimizations/Instruction-level parallelism: While it would be great to have some innovation into this field again, we’ve unfortunately hit the power wall, and thus we now obtain most of our performance benefits from multi-core.American Journal of Computer Architecture is aimed to publish all the latest and outstanding research articles, reviews and letters in all areas of bioinformatics and computational biology.It is a rigorously peer-reviewed forum for publishing early, high-impact results in the areas of computer architecture.I have had and still maintain a long standing interest in computer system design, encompassing machine architecture and organisation, operating systems with a focus on real time performance, IPC, File Systems and I/O Subsystems.This is a continuing thread of activity which started during the late 1980s, when I maintained VAX architecture machines and peripherals.