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Download the free NVIDIA PLASTER Deep Learning Framework whitepaper
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[av_heading heading=’PLASTER: A Framework for Deep Learning Performance’ tag=’h3′ style=’blockquote modern-quote’ size=” subheading_active=’subheading_below’ subheading_size=’15’ padding=’10’ color=” custom_font=” av-medium-font-size-title=” av-small-font-size-title=” av-mini-font-size-title=” av-medium-font-size=” av-small-font-size=” av-mini-font-size=” admin_preview_bg=”]
Whitepaper sponsored by NVIDIA
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“PLASTER” encompasses seven major challenges for delivering AI-based services.
- Programmability
- Latency
- Accuracy
- Size of Model
- Throughput
- Energy Efficiency
- Rate of Learning
This paper explores each of these AI challenges in the context of NVIDIA’s deep learning (DL) solutions. PLASTER as a whole is greater than the sum of its parts. Anyone interested in developing and deploying AI-based services should factor in all of PLASTER’s elements to arrive at a complete view of deep learning performance. Addressing the challenges described in PLASTER is important in any DL solution, and it is especially useful for developing and delivering the inference engines underpinning AI-based services. Each section of this paper includes a brief description of measurements for each framework component and an example of a customer leveraging NVIDIA solutions to tackle critical problems with machine learning.
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Download the free NVIDIA PLASTER Deep Learning Framework whitepaper
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