DataBloom

Here a few key sessions from industry leaders in media, delivery-on-demand, and retail at GTC Spring 2021.

Ensuring recommenders are meaningful, personalized, and relevant to a single customer is not easy. Scaling a personalized recommender experience to hundreds of thousands, or millions of customers, comes with unique challenges that data scientists and machine learning engineers tackle every day. Scaling challenges often provide obstacles to effective ETL, training, retraining, or deploying models into production.

To tackle these challenges, machine learning engineers and data scientists within the industry utilize a combination, or hybrid of tools, techniques, and algorithms. NVIDIA is committed to help streamline recommender workflows with Merlin, an open-source framework that is interoperable and designed to support machine learning engineers and data scientists with preprocessing, feature engineering, training, and inference. Merlin supports industry leaders who are tackling common recommender challenges as they provide relevant, impactful, and fresh recommenders at scale.

Here a few key sessions from industry leaders in media, delivery-on-demand, and retail at GTC Spring 2021.

• Learn How Tencent Deployed An Advertising System On The Merlin GPU Recommender Framework
  Learn how Tencent deployed their real advertising recommendation training with Merlin and achieved more than 7x speedup over the original TensorFlow solution on the same GPU platform.

• AI-First Social Media Feeds: A View From the Trenches
  Discusses efficient training of extremely large recommender models with billions of parameters distributed across multiple GPUs and workers as well as the importance of continual model updates in near-real time to deal with the key challenge of concept drift. The session includes how solutions in NVIDIA’s Merlin stack resolve key bottlenecks faced in general purpose deep learning frameworks.

• Personalization and Discovery at Postmates
  Covers the machine learning building blocks, relevant models developed in production, model optimizations to align with Postmates’ business objectives, and more.

• GPU-Accelerated Processing of Large Tabular Datasets and Distributed Neural Network Training with NVTabular+Dask+TensorFlow for Dynamic Pricing at Walmart
  Demonstrates how to use open-source tools like Dask, NVTabular, and TensorFlow to horizontally scale up GPU-accelerated training pipelines for large neural networks trained using tabular data.

• End-to-End Deployment of GPU Accelerated Recommender Systems: From ETL to Training to Inference
  Upon completion of this 4-hour in-depth workshop, attendees will be able to apply NVIDIA Merlin (NVTabular, HugeCTR and Triton Inference Server) to accelerate and scale their ETL, training and inference systems with GPUs.

Registration is free, visit the GTC website for more information.

Don’t blink. Accelerated computing is moving innovation forward faster than ever. And there’s no way to get smarter, quicker, about how it’s changing your world than to tune in to NVIDIA CEO Jensen Huang’s GTC keynote Monday, April 12, starting at 8:30 a.m. PT. The keynote, delivered again from the kitchen in Huang’s home, will Read article >

The post What Will NVIDIA CEO Jensen Huang Cook Up This Time at NVIDIA GTC? appeared first on The Official NVIDIA Blog.

We at NVIDIA are on a mission to bring the next generation data center vision to reality. Join us at NVIDIA GTC’21 (Apr 12-16, 2021) to witness the data center innovation we are pioneering.

As NVIDIA CEO Jensen Huang stated in last year’s GTC, “the data center is the new unit of computing.” Traditional way of using the server as the unit of computing is fading away quickly. More and more applications are moving to data centers that are located at the edge, in different availability zones or in private enterprise clouds. Modern workloads such as AI/ML, edge computing, cloud-native microservices and 5G services are becoming increasingly disaggregated, distributed and data hungry. These applications demand efficient, secure and accelerated computing and data processing across all the layers of the application stack. 

Computing accelerated by NVIDIA GPUs and data processing units (DPUs) is at the heart of modern data centers. DPUs are a game-changing new technology that accelerates GPU and CPU access to data while enabling software-defined, hardware-accelerated infrastructure. With DPUs, organizations can efficiently and effectively deploy networking, cyber security, and storage in virtualized as well as containerized environments.

We at NVIDIA are on a mission to bring the next generation data center vision to reality. Join us at NVIDIA GTC’21 (Apr 12-16, 2021) to witness the data center innovation we are pioneering.  Register for the top DPU sessions at GTC to learn how NVIDIA Networking solutions are powering the next generation data centers.

Palo Alto Networks and NVIDIA present  Accelerated 5G Security: DPU-Based Acceleration of Next-Generation Firewalls [S31671]

5G offers many new capabilities such as lower latency, higher reliability, throughput, agile service deployment through cloud-native architectures, greater device density, etc. A new approach is needed to achieve L7 security at these rates with software-based firewalls. Integrating Palo Alto Network next generation firewall with the NVIDIA DPU enables industry-leading high-performance security. NVIDIA’s Bluefield-2 DPU provides a rich set of network offload engines designed to address the acceleration needs of security-focused network functions in today’s most demanding markets such as 5G and the cloud.

Speakers:

• Sree Koratala, VP Product Management Mobility Security, Palo Alto Networks
• John McDowall, Senior Distinguished Engineer, Palo Alto Networks
• Ash Bhalgat, Senior Director, Cloud, Telco & Security Market Development, NVIDIA

China Mobile, Nokia and NVIDIA present Turbocharge Cloud-Native Applications with Virtual Data Plane Accelerated Networking [S31563]

Great progress has been made leveraging hardware to accelerate cloud networking for a wide range of cloud-based applications. This talk will examine how cloud networking for public cloud infrastructure as a service can be accelerated using the NVIDIA’s new open standards technology called virtual data plane acceleration (vDPA). In addition, this presentation will examine the early validation results and acceleration benefits of deploying NVIDIA ASAP² vDPA technology in China Mobile’s BigCloud cloud service.

Speakers:

• Sharko Cheng, Senior Network Architect, Cloud Networking Products Department, CMCC
• Mark Iskra, Director, Nokia/Nuage Networks
• Ash Bhalgat, Senior Director, Cloud, Telco & Security Market Development, NVIDIA

Red Hat and NVIDIA present  Implementing Virtual Network Offloading Using Open Source tools on BlueField-2 [S31380]

NVIDIA and Red Hat have been working together to provide an elegant and 100% open-source solution using the BlueField DPU for hardware offloading of the software-defined networking tasks in cloud-native environments. With BlueField DPUs, we can encrypt, encapsulate, switch, and route packets right on the DPU, effectively dedicating all the server’s processing capacity to running business applications. This talk will discuss typical use cases and demonstrate the performance advantages of using BlueField’s hardware offload capabilities with Red Hat Enterprise Linux and the Red Hat OpenShift container platform.

Speakers:

• Rashid Khan, Director of Networking, Red Hat
• Rony Efraim, Networking Software and Systems Architect, NVIDIA

NVIDIA DPU team presents  Program Data Center Infrastructure Acceleration with the Release of DOCA and the Latest DPU Software [S32205]

NVIDIA is releasing the first version of DOCA, a set of libraries, SDKs, and tools for programming the NVIDIA BlueField DPU, as well as the new version 3.6 of the DPU software. Together these enable new infrastructure acceleration and management features in BlueField, simplify programming and application integration. DPU developers can offload and accelerate networking, virtualization, security, and storage features including VirtIO for NFV/VNFs, BlueField SNAP for elastic storage virtualization, regular expression matching for malware detection, and deep packet inspection to enable sophisticated routing, firewall, and load-balancing applications.

Speakers:

• Ami Badani, VP Marketing, NVIDIA
• Ariel Kit, Director of Product Marketing for Networking, NVIDIA

F5/NGINX and NVIDIA presents  kTLS Hardware Offload Performance Benchmarking for NGINX Web Server [S31551]

Encrypted communication usage is steadily growing across most internet services. TLS is the leading security protocol implemented on top of TCP. kTLS (kernel TLS) serves as a unit that offers TLS operations support in the Linux kernel layer. It was introduced in kernel v4.13 as a software offload for user-space TLS libraries and was extended in kernel v4.18 with an infrastructure for performing hardware-accelerated encryption/decryption in the SmartNIC and DPUs. This session will review the life cycle of a hardware-offloaded kTLS connection and the driver-hardware interaction to support it while demonstrating and analyzing the significant performance gain by offloading kTLS operations to the hardware, using NGINX as the target workload and NVIDIA’s mlx5e driver on top of a ConnectX-6 Dx SmartNIC.

Speakers:

• Damian Curry, Business Development Technical Director, F5
• Bar Tuaf, Software engineer, NVIDIA

Register today for free and start building your schedule. 

Once you are signed in, you can explore all GTC conference topics here. Topics include areas of interest such as data center networking and virtualization, HPC, deep learning, data science, and autonomous machines, or industries including healthcare, public sector, retail, and telecommunications.

See you at the GTC’21!

Startups don’t just come from Silicon Valley — they hail from Senegal, Saudi Arabia, Pakistan, and beyond. And hundreds will take the stage at the GPU Technology Conference. GTC, running April 12-16, will spotlight developers and startups advancing AI in Africa, Latin America, Southeast Asia, and the Middle East. Registration is free, and provides access Read article >

The post World of Difference: GTC to Spotlight AI Developers in Emerging Markets appeared first on The Official NVIDIA Blog.

Data-hungry workloads such as machine learning and data analytics have become commonplace. To cope with these compute-intensive tasks, enterprises need accelerated servers that are optimized for high performance. Intel’s 3rd Gen Intel Xeon Scalable processors (code-named “Ice Lake”), launched today, are based on a new architecture that enables a major leap in performance and scalability. Read article >

The post NVIDIA-Powered Systems Ready to Bask in Ice Lake appeared first on The Official NVIDIA Blog.

Satinder Singh won the Jetson Project of the Month for DeepWay, an AI-based navigation assistance system for the visually impaired. The project, which runs on an NVIDIA Jetson Nano Developer Kit, monitors the path of a person and provides guidance to walk on the correct side and avoid any oncoming pedestrians.  In addition to the … Continued

Satinder Singh won the Jetson Project of the Month for DeepWay, an AI-based navigation assistance system for the visually impaired. The project, which runs on an NVIDIA Jetson Nano Developer Kit, monitors the path of a person and provides guidance to walk on the correct side and avoid any oncoming pedestrians. 

In addition to the Jetson Nano, Satinder’s setup includes an Arduino Nano, a webcam, two servo motors, a USB audio adapter, 3D printed eye-glasses and a few peripherals. The Arduino Nano is used to control the servo motors, which nudge the user in the correct direction by gently tapping them on either side of the head. If the Jetson Nano identifies pedestrians, a voice prompt sent through the USB audio adapter can be used to warn the user. 

To train his convolutional neural network, Satinder collected 10,000 images across three classes for left, center and right positions within a lane, and trained his model on a GPU-enabled virtual machine on Microsoft Azure. He used both PyTorch and Keras for training a U-net semantic segmentation model. After further analysis, he picked the U-Net model trained in Keras for its better performance.

DeepWay – Project Walk Through 

Satinder believes that his solution stands out among others because of its portability and affordability (plan including further optimizing it using NVIDIA TensorRT. We can’t wait to see how this project evolves.

The World Health Organization estimates at least 2.2 billion people around the world have a vision impairment. Many among this group would benefit from navigation aids. Open-source prototypes such as DeepWay foster innovation around these use-cases and are great examples of AI being used for social good.

If you’re interested in building your own ‘DeepWay’ or extending it, Satinder has shared the instructions and the code here.

When French classmates Guillaume Jourdain, Hugo Serrat and Jules Beguerie were looking at applying AI to agriculture in 2014 to form a startup, it was hardly a sure bet. It was early days for such AI applications, and people said it couldn’t be done. But farmers they spoke with wanted it. So they rigged together Read article >

The post Harvesting AI: Startup’s Weed Recognition for Herbicides Grows Yield for Farmers appeared first on The Official NVIDIA Blog.