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The downside to this technological progress is that computing has already hit a power and complexity wall.
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.
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.
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.Due to a particular lack of interest in architecture and related research topics by Australian funding bodies and prospective postgraduates, I have exploited this expertise primarily in Cl SIT BSE/BCS/MDC curriculum and courseware development since 2000, and in support of research in ad hoc networks and systems.For details of many of the industry projects I have worked on, refer main toolbar for The Walnut Kernel is a capability based operating system kernel that was developed in the Department of Computer Science at Monash University during the 1990s.An ANSI compliant standard IO library is used as an example of the expressive power of the system.The Wal NUT Password Capability System is a secure operating system design, which employs password capability techniques to control access to objects within the system.Deep learning is hugely popular in industry, and this research area will continue to grow, although I’m not entirely convinced that deep learning accelerators will actually overtake GPUs in the real-world.Still, if you’re interested in getting a computer architecture Ph D, this is where you will definitely get one.One of my professors was doing research in , although I haven’t been following the state-of-the-art regarding this topic.Datacenters: While maybe not as “hot” as Deep Learning, this is a hugely important and impactful field that will interest any large tech company that hosts their own data centers (eg. Without industry connections, research in this area is difficult, but any solutions in this area will literally save companies hundreds of millions of dollars.Hardware Security: Security is tremendously important in all computer science disciplines.However, exploits are far easier to implement at the software level as opposed to the hardware level, and having hardware solutions for security end up being rather impractical while achieving minimal benefit, in my opinion.