Hardware & devices

Video

Machine Learning for Placement-insensitive Inertial Motion Capture (ICRA 2018)

June 6, 2018 | Xuesu Xiao, Shuayb Zarar

Although existing inertial motion-capture systems work reasonably well (less than 10 degree error in Euler angles), their accuracy suffers when sensor positions change relative to the associated body segments (+/1 60 degree mean error and…

Machine Learning for Placement-insensitive Inertial Motion Capture (ICRA 2018)

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Publication

A Configurable Cloud-Scale DNN Processor for Real-Time AI

Jeremy Fowers, Kalin Ovtcharov, Michael Papamichael, Todd Massengill, Ming Liu, Daniel Lo, Shlomi Alkalay, Michael Haselman, Logan Adams, Mahdi Ghandi, Stephen Heil, Prerak Patel, Adam Sapek, Gabriel Weisz, Lisa Woods, Sitaram Lanka, Steve Reinhardt, Adrian Caulfield, Eric Chung, Doug Burger

Proceedings of the 45th International Symposium on Computer Architecture, 2018 | June 2018

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Publication

MAXelerator: FPGA Accelerator for Privacy Preserving Multiply-Accumulate (MAC) on Cloud Servers

Siam U. Hussain, Bita Rouhani, Mohammad Ghasemzadeh, Farinaz Koushanfar

Design Automation Conference (DAC) | June 2018

Publication

Computing with biological switches and clocks

Neil Dalchau, Gregory Szep, Rosa Hernansaiz-Ballesteros, Chris P Barnes, Luca Cardelli, Andrew Phillips, Attila Csikasz-Nagy

Natural Computing | June 2018

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Publication

Robox: an end-to-end solution to accelerate autonomous control in robotics

Jacob Sacks, Divya Mahajan, Richard C. Lawson, Hadi Esmaeilzadeh

2018 International Symposium on Computer Architecture | June 2018

Publication

The Locality Descriptor: A Holistic Cross-Layer Abstraction to Express Data Locality in GPUs

Nandita Vijaykumar, Eiman Ebrahimi, Kevin Hsieh, Phillip B. Gibbons, Onur Mutlu

International Symposium on Computer Architecture (ISCA) | June 2018

Publication

A Case for Richer Cross-layer Abstractions: Bridging the Semantic Gap with Expressive Memory

Nandita Vijaykumar, Abhilasha Jain, Diptesh Majumdar, Kevin Hsieh, Gennady Pekhimenko, Eiman Ebrahimi, Nastaran Hajinazar, Phillip B. Gibbons, Onur Mutlu

International Symposium on Computer Architecture (ISCA) | June 2018

Publication

Design and Implementation of a Smart Headband for Epileptic Seizure Detection and Its Verification Using Clinical Database

Shih-kai Lin, Isti Qomah, Yu-shan Lin, Herming Chiueh, Chin-Yew Lin

International Symposium on Circuits and Systems | May 2018

Publication

Machine Learning for Placement-insensitive Inertial Motion Capture

Xuesu Xiao, Shuayb Zarar

IEEE Int. Conf. Robotics and Automation (ICRA) | May 2018

Video Access Project

Video

Accelerating AI with Project Brainwave and Intel FPGAs

May 23, 2018 | Ted Way and Doug Burger

For the first time, data scientists and developers are able to take advantage of FPGAs in a way that’s natural to them. Azure Machine Learning hardware accelerated models powered by Project Brainwave with Intel FPGAs…

Accelerating AI with Project Brainwave and Intel FPGAs

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What’s Your Story: Weishung Liu | Microsoft Research Podcast

Microsoft at ASPLOS 2024: Advancing hardware and software for high-scale, secure, and efficient modern applications

Inclusive Digital Maker Futures for Children via Physical Computing | Event

RASCAL: Novel robotics for scalable and highly available automated storage and retrieval

Machine Learning for Placement-insensitive Inertial Motion Capture (ICRA 2018)

A Configurable Cloud-Scale DNN Processor for Real-Time AI

MAXelerator: FPGA Accelerator for Privacy Preserving Multiply-Accumulate (MAC) on Cloud Servers

Computing with biological switches and clocks

Robox: an end-to-end solution to accelerate autonomous control in robotics

The Locality Descriptor: A Holistic Cross-Layer Abstraction to Express Data Locality in GPUs

A Case for Richer Cross-layer Abstractions: Bridging the Semantic Gap with Expressive Memory

Design and Implementation of a Smart Headband for Epileptic Seizure Detection and Its Verification Using Clinical Database

Machine Learning for Placement-insensitive Inertial Motion Capture

Accelerating AI with Project Brainwave and Intel FPGAs

Hardware & devices

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