• Home
  • Events Calendar
  • Blueprint Guidelines
  • Privacy Policy
  • Subscribe to Daily Newsletter
  • NextGenInfra.io
No Result
View All Result
Converge Digest
Friday, April 17, 2026
  • Home
  • Events Calendar
  • Blueprint Guidelines
  • Privacy Policy
  • Subscribe to Daily Newsletter
  • NextGenInfra.io
No Result
View All Result
Converge Digest
No Result
View All Result

Home » NVIDIA Unveils GPU Accelerators for Deep Learning AI

NVIDIA Unveils GPU Accelerators for Deep Learning AI

April 6, 2016
in All
A A

NVIDIA unveiled its most advanced accelerator to date — the Tesla P100 — based on Pascal architecture and composed of an array of Graphics Processing Clusters (GPCs), Streaming Multiprocessors (SMs), and memory controllers. The Tesla P100, which is implemented in 16nm FinFET on a massive 610mm2die, enables a new class of servers that can deliver the performance of hundreds of CPU server nodes.

NVIDIA said its accelerator brings five breakthroughs:

  • NVIDIA Pascal architecture for exponential performance leap — a Pascal-based Tesla P100 solution delivers over a 12x increase in neural network training performance compared with a previous-generation NVIDIA Maxwell-based solution.
  • NVIDIA NVLink for maximum application scalability — The NVIDIA NVLink high-speed GPU interconnect scales applications across multiple GPUs, delivering a 5x acceleration in bandwidth compared to today’s best-in-class solution. Up to eight Tesla P100 GPUs can be interconnected with NVLink to maximize application performance in a single node, and IBM has implemented NVLink on its POWER8 CPUs for fast CPU-to-GPU communication.
  • 16nm FinFET for unprecedented energy efficiency — with 15.3 billion transistors built on 16 nanometer FinFET fabrication technology, the Pascal GPU is the world’s largest FinFET chip ever built.
  • CoWoS with HBM2 for big data workloads — the Pascal architecture unifies processor and data into a single package to deliver unprecedented compute efficiency. An innovative approach to memory design, Chip on Wafer on Substrate (CoWoS) with HBM2, provides a 3x boost in memory bandwidth performance, or 720GB/sec, compared to the Maxwell architecture.
  • New AI algorithms for peak performance — new half-precision instructions deliver more than 21 teraflops of peak performance for deep learning.

At its GPU Technology conference in San Jose, Nvidia also unveiled its DGX-1 Deep Learning supercomputer. It is a turnkey system that integrates eight Tesla P100 GPU accelerators, delivering the equivalent throughput of 250 x86 servers.

“Artificial intelligence is the most far-reaching technological advancement in our lifetime,” said Jen-Hsun Huang, CEO and co-founder of NVIDIA. “It changes every industry, every company, everything. It will open up markets to benefit everyone. Data scientists and AI researchers today spend far too much time on home-brewed high performance computing solutions. The DGX-1 is easy to deploy and was created for one purpose: to unlock the powers of superhuman capabilities and apply them to problems that were once unsolvable.”

“NVIDIA GPU is accelerating progress in AI. As neural nets become larger and larger, we not only need faster GPUs with larger and faster memory, but also much faster GPU-to-GPU communication, as well as hardware that can take advantage of reduced-precision arithmetic. This is precisely what Pascal delivers,” said Yann LeCun, director of AI Research at Facebook.

http://nvidianews.nvidia.com

Tags: #AIBlueprint columnsGPUNvidiaSuperComputing
ShareTweetShare
Previous Post

Ericsson to Acquire NodePrime for Hyperscale Data Center Automation

Next Post

ZTE’s Revenue Tops RMB100.1 Billion in 2015

Staff

Staff

Related Posts

OCP Expands AI Initiative with Contributions from NVIDIA and Meta
Semiconductors

Arm Extends Neoverse With NVIDIA NVLink Fusion

November 17, 2025
Deutsche Telekom Looks to NVIDIA for €1B Industrial AI Cloud
AI Infrastructure

Deutsche Telekom Looks to NVIDIA for €1B Industrial AI Cloud

November 6, 2025
Forescout Unveils Real-Time Detection Tech for Non-Quantum-Safe Encryption
Quantum

NVQLink: NVIDIA’s Bridge to Quantum Supercomputing

November 1, 2025
NVIDIA Fuels Korea’s AI Factory Boom
AI Infrastructure

NVIDIA Fuels Korea’s AI Factory Boom

November 1, 2025
The Megawatt Shift: NVIDIA’s 800 VDC Strategy
Data Centers

The Megawatt Shift: NVIDIA’s 800 VDC Strategy

November 1, 2025
NVIDIA Launches BlueField-4 DPU
Data Centers

NVIDIA Launches BlueField-4 DPU

October 30, 2025
Next Post
ZTE’s Revenue Tops RMB100.1 Billion in 2015

ZTE's Revenue Tops RMB100.1 Billion in 2015

Please login to join discussion

Categories

  • 5G / 6G / Wi-Fi
  • AI Infrastructure
  • All
  • Automotive Networking
  • Blueprints
  • Clouds and Carriers
  • Data Centers
  • Enterprise
  • Explainer
  • Feature
  • Financials
  • Last Mile / Middle Mile
  • Legal / Regulatory
  • Optical
  • Quantum
  • Research
  • Security
  • Semiconductors
  • Space
  • Start-ups
  • Subsea
  • Sustainability
  • Video
  • Webinars

Archives

Tags

5G All AT&T Australia AWS Blueprint columns BroadbandWireless Broadcom China Ciena Cisco Data Centers Dell'Oro Ericsson FCC Financial Financials Huawei Infinera Intel Japan Juniper Last Mile Last Mille LTE Mergers and Acquisitions Mobile NFV Nokia Optical Packet Systems PacketVoice People Regulatory Satellite SDN Service Providers Silicon Silicon Valley StandardsWatch Storage TTP UK Verizon Wi-Fi
Converge Digest

A private dossier for networking and telecoms

Follow Us

  • Home
  • Events Calendar
  • Blueprint Guidelines
  • Privacy Policy
  • Subscribe to Daily Newsletter
  • NextGenInfra.io

© 2025 Converge Digest - A private dossier for networking and telecoms.

No Result
View All Result
  • Home
  • Events Calendar
  • Blueprint Guidelines
  • Privacy Policy
  • Subscribe to Daily Newsletter
  • NextGenInfra.io

© 2025 Converge Digest - A private dossier for networking and telecoms.

This website uses cookies. By continuing to use this website you are giving consent to cookies being used. Visit our Privacy and Cookie Policy.
Go to mobile version