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Verification and testing of hardware heavily relies on cycle-accurate simulation of RTL.As single-processor performance is growing only slowly, conventional, single-threaded RTL simulation is becoming impractical for increasingly complex chip designs and s ...
EPFL2024
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Analog in-memory computing (AIMC) cores offers significant performance and energy benefits for neural network inference with respect to digital logic (e.g., CPUs). AIMCs accelerate matrix-vector multiplications, which dominate these applications’ run-time. ...
A system and method of coupling a Branch Target Buffer (BTB) content of a BTB with an instruction cache content of an instruction cache. The method includes: tagging a plurality of target buffer entries that belong to branches within a same instruction blo ...
While domain adaptation has been used to improve the performance of object detectors when the training and test data follow different distributions, previous work has mostly focused on two-stage detectors. This is because their use of region proposals make ...
Additive manufacturing (AM) of passive microwave components is of high interest for the cost-effective and rapid prototyping or manufacture of devices with complex geometries. Here, we present an experimental study on the properties of recently demonstrate ...
Large arrays of the same nonvolatile memories (NVM) being developed for Storage-Class Memory (SCM) such as Phase Change Memory (PCM) and Resistance RAM (ReRAM) - can also be used in non-Von Neumann neuromorphic computational schemes, with device conductanc ...
The physical or engineering assets within modern industries have consistently been considered as the core elements of significant value that constitute the backbone for success and overall growth. Ensuring the optimal performance of an asset is a crucial a ...
The implementation of a classical control infrastructure for large-scale quantum computers is challenging due to the need for integration and processing time, which is constrained by coherence time. We propose a cryogenic reconfigurable platform as the hea ...
2017
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Transformer models have achieved impressive results in various AI scenarios, ranging from vision to natural language processing. However, their computational complexity and their vast number of parameters hinder their implementations on resource-constraine ...
2023
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With the spread of cloud services and Internet of Things concept, there is a popularization of machine learning and artificial intelligence based analytics in our everyday life. However, an efficient deployment of these data-intensive services requires per ...