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Month: April 2024
PolyThrottle: Energy-efficient Neural Network Inference on Edge Devices: Experimental Results
:::info This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license. Authors: (1) Minghao Yan, University of Wisconsin-Madison; (2) Hongyi Wang, Carnegie Mellon University; (3) Shivaram Venkataraman, myan@cs.wisc.edu. ::: Table of Links Abstract & Introduction Motivation Opportunities Architecture Overview Proble Formulation: Two-Phase Tuning Modeling Workload Interference Experiments Conclusion & References A. Hardware Details … Read more
PolyThrottle: Energy-efficient Neural Network Inference on Edge Devices: Opportunities
:::info This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license. Authors: (1) Minghao Yan, University of Wisconsin-Madison; (2) Hongyi Wang, Carnegie Mellon University; (3) Shivaram Venkataraman, myan@cs.wisc.edu. ::: Table of Links Abstract & Introduction Motivation Opportunities Architecture Overview Proble Formulation: Two-Phase Tuning Modeling Workload Interference Experiments Conclusion & References A. Hardware Details … Read more
PolyThrottle: Energy-efficient Neural Network Inference on Edge Devices: Motivation
:::info This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license. Authors: (1) Minghao Yan, University of Wisconsin-Madison; (2) Hongyi Wang, Carnegie Mellon University; (3) Shivaram Venkataraman, myan@cs.wisc.edu. ::: Table of Links Abstract & Introduction Motivation Opportunities Architecture Overview Proble Formulation: Two-Phase Tuning Modeling Workload Interference Experiments Conclusion & References A. Hardware Details … Read more
PolyThrottle: Energy-efficient Neural Network Inference on Edge Devices: Experiments
:::info This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license. Authors: (1) Minghao Yan, University of Wisconsin-Madison; (2) Hongyi Wang, Carnegie Mellon University; (3) Shivaram Venkataraman, myan@cs.wisc.edu. ::: Table of Links Abstract & Introduction Motivation Opportunities Architecture Overview Proble Formulation: Two-Phase Tuning Modeling Workload Interference Experiments Conclusion & References A. Hardware Details … Read more
PolyThrottle: Energy-efficient Neural Network Inference on Edge Devices: Conclusion & References
:::info This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license. Authors: (1) Minghao Yan, University of Wisconsin-Madison; (2) Hongyi Wang, Carnegie Mellon University; (3) Shivaram Venkataraman, myan@cs.wisc.edu. ::: Table of Links Abstract & Introduction Motivation Opportunities Architecture Overview Proble Formulation: Two-Phase Tuning Modeling Workload Interference Experiments Conclusion & References A. Hardware Details … Read more
PolyThrottle: Energy-efficient Neural Network Inference on Edge Devices: Hardware Details
:::info This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license. Authors: (1) Minghao Yan, University of Wisconsin-Madison; (2) Hongyi Wang, Carnegie Mellon University; (3) Shivaram Venkataraman, myan@cs.wisc.edu. ::: Table of Links Abstract & Introduction Motivation Opportunities Architecture Overview Proble Formulation: Two-Phase Tuning Modeling Workload Interference Experiments Conclusion & References A. Hardware Details … Read more
PolyThrottle: Energy-efficient Neural Network Inference on Edge Devices: Arithmetic Intensity
:::info This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license. Authors: (1) Minghao Yan, University of Wisconsin-Madison; (2) Hongyi Wang, Carnegie Mellon University; (3) Shivaram Venkataraman, myan@cs.wisc.edu. ::: Table of Links Abstract & Introduction Motivation Opportunities Architecture Overview Proble Formulation: Two-Phase Tuning Modeling Workload Interference Experiments Conclusion & References A. Hardware Details … Read more
Modeling Workload Interference
:::info This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license. Authors: (1) Minghao Yan, University of Wisconsin-Madison; (2) Hongyi Wang, Carnegie Mellon University; (3) Shivaram Venkataraman, myan@cs.wisc.edu. ::: Table of Links Abstract & Introduction Motivation Opportunities Architecture Overview Proble Formulation: Two-Phase Tuning Modeling Workload Interference Experiments Conclusion & References A. Hardware Details … Read more
Proble Formulation: Two-Phase Tuning
:::info This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license. Authors: (1) Minghao Yan, University of Wisconsin-Madison; (2) Hongyi Wang, Carnegie Mellon University; (3) Shivaram Venkataraman, myan@cs.wisc.edu. ::: Table of Links Abstract & Introduction Motivation Opportunities Architecture Overview Proble Formulation: Two-Phase Tuning Modeling Workload Interference Experiments Conclusion & References A. Hardware Details … Read more
PolyThrottle: Energy-efficient Neural Network Inference on Edge Devices: Abstract & Introduction
:::info This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license. Authors: (1) Minghao Yan, University of Wisconsin-Madison; (2) Hongyi Wang, Carnegie Mellon University; (3) Shivaram Venkataraman, myan@cs.wisc.edu. ::: Table of Links Abstract & Introduction Motivation Opportunities Architecture Overview Proble Formulation: Two-Phase Tuning Modeling Workload Interference Experiments Conclusion & References A. Hardware Details … Read more
PolyThrottle: Energy-efficient Neural Network Inference on Edge Devices: Predictor Analysis
:::info This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license. Authors: (1) Minghao Yan, University of Wisconsin-Madison; (2) Hongyi Wang, Carnegie Mellon University; (3) Shivaram Venkataraman, myan@cs.wisc.edu. ::: Table of Links Abstract & Introduction Motivation Opportunities Architecture Overview Proble Formulation: Two-Phase Tuning Modeling Workload Interference Experiments Conclusion & References A. Hardware Details … Read more
PolyThrottle: Energy-efficient Neural Network Inference on Edge Devices: Architecture Overview
:::info This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license. Authors: (1) Minghao Yan, University of Wisconsin-Madison; (2) Hongyi Wang, Carnegie Mellon University; (3) Shivaram Venkataraman, myan@cs.wisc.edu. ::: Table of Links Abstract & Introduction Motivation Opportunities Architecture Overview Proble Formulation: Two-Phase Tuning Modeling Workload Interference Experiments Conclusion & References A. Hardware Details … Read more
Indeed announces AI-powered work experience writer and support for multiple resumes
Hiring portal Indeed has redesigned the profile page for users, allowing individuals to use an AI-powered writer to fill up work experience and also added support for multiple resumes. The company has also launched a set of smart sourcing suites for recruiters with features like AI-powered candidate summaries and custom messages. Recruiter Holdings-owned Indeed is … Read more
How Meta’s global head of safety approaches online age verification
Illustration: Nick Barclay / The Verge “The ability to know somebody’s age and try to protect privacy at the same time can be challenging,” says Meta’s Global Head of Safety Antigone Davis. Meta has been advocating for app store operators like Apple and Google to be in charge of verifying users’ ages and soliciting parental … Read more
Ethena Labs’ ENA Token Goes Live, Starts Trading at 64 Cents
Ethena has invited holders of USDe to claim their share of the airdrop of 750 million ENA tokens, equating to 5% of the total supply.
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Bitcoin Price Plunges Below $67,000, Crypto Market Sees $426 Million in Liquidations
The wider crypto market fell in lockstep with Bitcoin, with all of the top 30 coins barring stablecoins posting losses.
Debian Git Monorepo
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TRON Foundation, Justin Sun Ask U.S. Court to Dismiss SEC Lawsuit
The TRON Foundation and Justin Sun asked a New York court to dismiss an SEC lawsuit, arguing that the regulator failed to establish that the court has jurisdiction over the foreign defendants.
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Crypto Market Setup Looks Positive for Second Quarter: Coinbase
The bitcoin halving, expected in mid-April, remains the main supply-side event, the report said.
Crypto Exchange Deribit’s Dubai-Based Unit Wins Conditional VASP License
Obtaining the full VARA spot and derivatives license is an important next step in our efforts to raise the overall quality & governance standards of our platform, exchange’s new CEO Luuk Strikers told CoinDesk.