Harnessing artificial intelligence for the next generation of 3D printed medicines
Artificial intelligence (AI) is redefining how we exist in the world. In almost every sector of
society, AI is performing tasks with super-human speed and intellect; from the prediction of …
society, AI is performing tasks with super-human speed and intellect; from the prediction of …
A survey of machine learning for computer architecture and systems
It has been a long time that computer architecture and systems are optimized for efficient
execution of machine learning (ML) models. Now, it is time to reconsider the relationship …
execution of machine learning (ML) models. Now, it is time to reconsider the relationship …
Power-performance modeling on asymmetric multi-cores
M Pricopi, TS Muthukaruppan… - … and Synthesis for …, 2013 - ieeexplore.ieee.org
Asymmetric multi-core architectures have recently emerged as a promising alternative in a
power and thermal constrained environment. They typically integrate cores with different …
power and thermal constrained environment. They typically integrate cores with different …
A practical method for estimating performance degradation on multicore processors, and its application to hpc workloads
When multiple threads or processes run on a multi-core CPU they compete for shared
resources, such as caches and memory controllers, and can suffer performance degradation …
resources, such as caches and memory controllers, and can suffer performance degradation …
Analytical processor performance and power modeling using micro-architecture independent characteristics
S Van den Steen, S Eyerman… - IEEE Transactions …, 2016 - ieeexplore.ieee.org
Optimizing processors for (a) specific application (s) can substantially improve energy-
efficiency. With the end of Dennard scaling, and the corresponding reduction in energy …
efficiency. With the end of Dennard scaling, and the corresponding reduction in energy …
A survey of machine learning applied to computer architecture design
DD Penney, L Chen - arXiv preprint arXiv:1909.12373, 2019 - arxiv.org
Machine learning has enabled significant benefits in diverse fields, but, with a few
exceptions, has had limited impact on computer architecture. Recent work, however, has …
exceptions, has had limited impact on computer architecture. Recent work, however, has …
Predicting new workload or CPU performance by analyzing public datasets
The marketplace for general-purpose microprocessors offers hundreds of functionally similar
models, differing by traits like frequency, core count, cache size, memory bandwidth, and …
models, differing by traits like frequency, core count, cache size, memory bandwidth, and …
Micro-architecture independent analytical processor performance and power modeling
S Van den Steen, S De Pestel, M Mechri… - … Analysis of Systems …, 2015 - ieeexplore.ieee.org
Optimizing processors for specific application (s) can substantially improve energy-
efficiency. With the end of Dennard scaling, and the corresponding reduction in …
efficiency. With the end of Dennard scaling, and the corresponding reduction in …
Framework for a productive performance optimization
Modern supercomputers deliver large computational power, but it is difficult for an
application to exploit such power. One factor that limits the application performance is the …
application to exploit such power. One factor that limits the application performance is the …
Learning Independent Program and Architecture Representations for Generalizable Performance Modeling
This paper proposes PerfVec, a novel deep learning-based performance modeling
framework that learns high-dimensional, independent/orthogonal program and …
framework that learns high-dimensional, independent/orthogonal program and …