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EDEN: Enabling energy-efficient, high-performance deep neural network inference using approximate DRAM
The effectiveness of deep neural networks (DNN) in vision, speech, and language
processing has prompted a tremendous demand for energy-efficient high-performance DNN …
processing has prompted a tremendous demand for energy-efficient high-performance DNN …
DRHEFT: Deadline-constrained reliability-aware HEFT algorithm for real-time heterogeneous MPSoC systems
Heterogeneous multiprocessor system-on-chips (MPSoCs) are suitable platforms for real-
time embedded applications that require powerful parallel processing capability as well as …
time embedded applications that require powerful parallel processing capability as well as …
Approximate computing with partially unreliable dynamic random access memory-approximate DRAM
In the context of approximate computing, Approximate Dynamic Random Access Memory
(ADRAM) enables the tradeoff between energy efficiency, performance and reliability. The …
(ADRAM) enables the tradeoff between energy efficiency, performance and reliability. The …
Omitting refresh: A case study for commodity and wide i/o drams
Dynamic Random Access Memories (DRAM) have a big impact on performance and
contribute significantly to the total power consumption in systems ranging from mobile …
contribute significantly to the total power consumption in systems ranging from mobile …
Efficient reliability management in SoCs-an approximate DRAM perspective
In today's computing systems Dynamic Random Access Memories (DRAMs) have a large
influence on performance and contribute significantly to the total power consumption. Thus …
influence on performance and contribute significantly to the total power consumption. Thus …
Using run-time reverse-engineering to optimize DRAM refresh
The overhead of DRAM refresh is increasing with each density generation. To help offset
some of this overhead, JEDEC designed the modern Auto-Refresh command with a highly …
some of this overhead, JEDEC designed the modern Auto-Refresh command with a highly …
ADROIT: An Adaptive Dynamic Refresh Optimization Framework for DRAM Energy Saving In DNN Training
To achieve high accuracy, DNN training usually consumes and generates myriads of data,
which requires a large DRAM for efficient processing. The refresh power consumption in …
which requires a large DRAM for efficient processing. The refresh power consumption in …
Cross-layer refresh mitigation for efficient and reliable DRAM systems: A comparative study
DRAM is a crucial component in computing systems, and is expected to be even more
important as data-intensive applications become more prominent. A key challenge in …
important as data-intensive applications become more prominent. A key challenge in …
[PDF][PDF] Efficient fault tolerance for selected scientific computing algorithms on heterogeneous and approximate computer architectures
A Schöll - 2018 - core.ac.uk
Simulation technology and scientific computing play an essential role in the majority of
scientific domains and have become established techniques to solve central challenges in …
scientific domains and have become established techniques to solve central challenges in …
Intelligent Vision Systems: Exploring the State-of-the-Art and Opportunities for the Future
Vision and video applications are becoming pervasive in mobile and embedded systems.
Consumer wearable devices require capabilities for real-time video analytics and prolonged …
Consumer wearable devices require capabilities for real-time video analytics and prolonged …