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Chasing carbon: The elusive environmental footprint of computing
Given recent algorithm, software, and hardware innovation, computing has enabled a
plethora of new applications. As computing becomes increasingly ubiquitous, however, so …
plethora of new applications. As computing becomes increasingly ubiquitous, however, so …
A hierarchical framework of cloud resource allocation and power management using deep reinforcement learning
Automatic decision-making approaches, such as reinforcement learning (RL), have been
applied to (partially) solve the resource allocation problem adaptively in the cloud computing …
applied to (partially) solve the resource allocation problem adaptively in the cloud computing …
Machine learning for power, energy, and thermal management on multicore processors: A survey
Due to the high integration density and roadblock of voltage scaling, modern multicore
processors experience higher power densities than previous technology scaling nodes …
processors experience higher power densities than previous technology scaling nodes …
Energy-efficient datacenters
Pervasive use of cloud computing and the resulting rise in the number of datacenters and
hosting centers (that provide platform or software services to clients who do not have the …
hosting centers (that provide platform or software services to clients who do not have the …
Reinforcement learning-assisted garbage collection to mitigate long-tail latency in SSD
NAND flash memory is widely used in various systems, ranging from real-time embedded
systems to enterprise server systems. Because the flash memory has erase-before-write …
systems to enterprise server systems. Because the flash memory has erase-before-write …
Application and thermal-reliability-aware reinforcement learning based multi-core power management
Power management through dynamic voltage and frequency scaling (DVFS) is one of the
most widely adopted techniques. However, it impacts application reliability (due to soft …
most widely adopted techniques. However, it impacts application reliability (due to soft …
Opportunities for machine learning in electronic design automation
The rise of machine learning (ML) has introduced many opportunities for computer-aided-
design, VLSI design, and their intersection. Related to computer-aided design, we review …
design, VLSI design, and their intersection. Related to computer-aided design, we review …
Optimal DPM and DVFS for frame-based real-time systems
Dynamic Power Management (DPM) and Dynamic Voltage and Frequency Scaling (DVFS)
are popular techniques for reducing energy consumption. Algorithms for optimal DVFS exist …
are popular techniques for reducing energy consumption. Algorithms for optimal DVFS exist …
Model-free reinforcement learning and bayesian classification in system-level power management
To cope with uncertainties and variations that emanate from hardware and/or application
characteristics, dynamic power management (DPM) frameworks must be able to learn about …
characteristics, dynamic power management (DPM) frameworks must be able to learn about …
LifeGuard: A reinforcement learning-based task map** strategy for performance-centric aging management
Device scaling to subdeca nanometer has pushed device aging as a primary design
concern. In manycore systems, inevitable process variation further adds to delay …
concern. In manycore systems, inevitable process variation further adds to delay …