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(Created page with "Who are we What do we do Where to find us ===Available Projects=== <DynamicPageList> category = Available category = Digital category = Acceleration and Transprecision suppr...")
 
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Who are we
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[[File:NVIDIA Tesla V100.jpg|thumb|right|A NVIDIA Tesla V100 GP-GPU. This cutting-edge accelerator provides huge computational power on a [https://arstechnica.com/gadgets/2017/05/nvidia-tesla-v100-gpu-details/ massive 800 mm² die].]]
What do we do
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[[File:Google Cloud TPU.png|thumb|right|Google's Cloud TPU (Tensor Processing Unit). This machine learning accelerator can do one thing extremely well: multiply-accumulate operations.]]
Where to find us
 
  
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Accelerators are the backbone of big data and scientific computing. While general purpose processor architectures such as Intel's x86 provide good performance across a wide variety of applications, it is only since the advent of general purpose GPUs that many computationally demanding tasks have become feasible. Since these GPUs support a much narrower set of operations, it is easier to optimize the architecture to make them more efficient. Such accelerators are not limited to high performance sector alone. In low power computing, they allow complex tasks such as computer vision or cryptography to be performed under a very tight power budget. Without a dedicated accelerator, these tasks would not be feasible.
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===Who We Are===
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====Francesco Conti====
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* [mailto:fconti@iis.ee.ethz.ch fconti@iis.ee.ethz.ch]
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* ETZ J78
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====Stefan Mach====
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* [mailto:smach@iis.ee.ethz.ch smach@iis.ee.ethz.ch]
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* ETZ J89
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====Fabian Schuiki====
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* [mailto:fschuiki@iis.ee.ethz.ch fschuiki@iis.ee.ethz.ch]
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* ETZ J89
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====Manuel Eggimann====
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* [mailto:meggiman@iis.ee.ethz.ch meggiman@iis.ee.ethz.ch]
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* ETZ J68
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====Luca Bertaccini====
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* [mailto:lbertaccini@iis.ee.ethz.ch lbertaccini@iis.ee.ethz.ch]
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* ETZ J78
  
 
===Available Projects===
 
===Available Projects===
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===Completed Projects===
 
===Completed Projects===
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[[File:Selene.jpg|thumb|right|The Logarithmic Number Unit chip [http://asic.ethz.ch/2014/Selene.html Selene].]]
 
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<DynamicPageList>
 
category = Completed
 
category = Completed

Revision as of 00:20, 1 November 2020

A NVIDIA Tesla V100 GP-GPU. This cutting-edge accelerator provides huge computational power on a massive 800 mm² die.
Google's Cloud TPU (Tensor Processing Unit). This machine learning accelerator can do one thing extremely well: multiply-accumulate operations.

Accelerators are the backbone of big data and scientific computing. While general purpose processor architectures such as Intel's x86 provide good performance across a wide variety of applications, it is only since the advent of general purpose GPUs that many computationally demanding tasks have become feasible. Since these GPUs support a much narrower set of operations, it is easier to optimize the architecture to make them more efficient. Such accelerators are not limited to high performance sector alone. In low power computing, they allow complex tasks such as computer vision or cryptography to be performed under a very tight power budget. Without a dedicated accelerator, these tasks would not be feasible.

Who We Are

Francesco Conti

Stefan Mach

Fabian Schuiki

Manuel Eggimann

Luca Bertaccini

Available Projects


Projects In Progress


Completed Projects

The Logarithmic Number Unit chip Selene.