- Tutorial on Hardware Architectures for Deep Neural Networks : How to leverage hardware for accelerating machine learning processes.
- A Survey on Homomorphic Encryption Schemes : this paper presents a thorough survey of the state of homomorphic encryption schemes. Homomorphic encryption allows manipulation of the encrypted data without the need to decrypt it. This will allow when hardware will be fast enough to deal with the complexity of the operations, to have a true secure distributed multitenant database. As no operation on the hosting side will require clear text decryption of the data and everything can be done securely on the client side.
- Efficient Methods and Hardware for Deep Learning : Standford lecture where guest lecturer Song Han present algorithms and specialized hardware (FPGA, GPU, ASIC, etc..) that can be used to accelerate training and inference of deep learning workloads. [video]
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Showing posts with label acceleration. Show all posts
Showing posts with label acceleration. Show all posts
Tuesday, October 10, 2017
[Links of the Day] 10/10/2017 : Machine Learning Hardware acceleration , Homomorphic encryption
Labels:
acceleration
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asic
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deep learning
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encryption
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fpga
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gpgpu
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hardware
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homomorphic
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links of the day
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machine learning
Friday, March 13, 2015
Links of the day 13 - 03 - 2015
Today's links 13/03/2015: machine learning , Time-Series and Geospatial database, Write acceleration for virtual environment
- Clustered Fault Tolerant Write Acceleration in a Virtualized Environment : PernixData present a fault tolerant host-side flash write acceleration layer that seamlessly integrates with the virtualized environment while preserving dynamic resource management and high availability
- Machine Learning for Programming : Peter Norvig keynotes on using machine learning techniques to solve more general software problems, helping both the advanced programmer and the novice one.
- Time-Series Database Requirements : the author present its own ideas about what constitutes a good time-series database
- Why Are Geospatial Databases So Hard To Build? : the root of the problem is that the internals of a database engine designed for traditional “text and numbers” data models, which is virtually all of them, has very little in common with a database engine designed for real-time spatial data models.
Labels:
acceleration
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database
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geo-spatial
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links of the day
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storage
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time series
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virtualization
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