Versa Networks announced a new capability connecting Versa Secure SD-WAN, on-premises, and cloud branches with applications and resources in Amazon Web Services (AWS) using the new high-performance AWS Transit Gateway Connect feature, an AWS Transit Gateway attachment type that enables AWS customers to connect third-party SD-WAN hubs and network virtual appliances with AWS Transit Gateway.

As a result, businesses can now benefit from AWS Transit Gateway peering connections for up to 5 Gbps of bandwidth per GRE tunnel, while continuing to leverage the high-performance, application and SLA-aware network via the Versa Traffic Engineered Protocol.

AWS Transit Gateway connects Amazon Virtual Private Clouds (Amazon VPCs) and on-premises networks through a central hub. Versa Director now integrates with AWS Transit Gateway Connect APIs to deliver an automated, one-click solution for connecting Versa Secure SD-WAN, on-premises and multi-cloud branch locations to each other and with Amazon VPCs.

Versa customers can now easily connect Versa Secure SD-WAN with AWS Transit Gateway for a high-performance and simplified connection between their branch offices, applications and resources in Amazon VPCs.

The native integration with AWS Transit Gateway Connect allows customers to deploy high-bandwidth Versa Cloud Gateways in AWS leveraging the Versa centralized management and orchestration. Customers can also leverage Versa Analytics and monitoring capabilities for end-to-end visibility and tracking of application performance all in one dashboard.

“Organizations are rapidly migrating their applications and data to AWS,” said Mayumi Hiramatsu, Vice President, Amazon EC2 Networking, Amazon Web Services, Inc. “We are pleased to work with Versa Networks so customers can leverage the new AWS Transit Gateway Connect feature for seamless connectivity between their branch offices and their Amazon VPCs.”

By integrating with AWS Transit Gateway Connect, Versa enables customers to monitor user traffic when accessing cloud-based AWS applications over Versa Secure SD-WAN or using AWS as the transit network to connect on-premise branches.

Customers also benefit from Layer-7 application and SLA-aware networking features, and performance enhancing features such as application acceleration provided by Versa Secure SD-WAN. Versa Secure SD-WAN is uniquely positioned to leverage AWS Transit Gateway due to its differentiated architecture, Versa Traffic Engineered Protocol, and robust feature set.

New Versa Director capabilities integrate with AWS Transit Gateway Connect APIs using workflows and automation to abstract the configuration requirements of AWS and deliver a simplified, guided experience for configuration.

AWS Transit Gateway Connect seamlessly integrates into customers’ enterprise networking architecture as a transit hub to connect their branches with each other and with Amazon VPCs.

“Versa’s customer base is increasingly leveraging cloud services for hosting applications and connecting branch offices using high quality links,” said Dogu Narin, Head of Product Management for Versa Networks.

“This new integration with AWS Transit Gateway Connect enables customers to benefit from a very high-performance peer-to-peer network. This will be particularly important for our global multi-national customers that require scalable cloud-delivered and highly reliable connectivity between globally distributed branches.”

Versa is the leader in SASE and Secure SD-WAN, uniquely combining full-featured SD-WAN, comprehensive integrated security, scalable advanced routing, genuine multi-tenancy, and sophisticated analytics on-premises and in the cloud to meet WAN Edge requirements for small to very large enterprises, as well as Service Providers.

Versa enables secure, scalable, and reliable enterprise-wide networking, increasing multi-cloud application performance and dramatically driving down costs (CapEx and OpEx). Versa Secure SD-WAN and SASE are available on-premises, hosted through Service Providers, cloud-delivered, and via the Versa Titan service for Lean IT.

AWS has announced the launch of its next-generation GPU-equipped instances. The P4d instances arrive nearly a decade after AWS first launched its Cluster GPU instances, which were launched in late 2010, and promise better performance at a lower cost.

“Today I would like to tell you about the new GPU-equipped P4 instances,” Jeff Barr, Chief Evangelist for AWS, said. “These instances are powered by the latest Intel Cascade Lake processors and feature eight of the latest NVIDIA A100 Tensor Core GPUs, each connected to all of the others by NVLink and with support for NVIDIA GPUDirect. With 2.5 PetaFLOPS of floating point performance and 320 GB of high-bandwidth GPU memory, the instances can deliver up to 2.5x the deep learning performance, and up to 60% lower cost to train when compared to P3 instances.”

The new instances come with 1.1 TB of system memory and 8 TB of SSD storage. They are also equipped with four 100 Gbps network connections, 320 GB of high-bandwidth GPU memory and are available for an on-demand price of $32.77 per hour.

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For large-scale enterprises, there is an opportunity to create an on-demand EC2 UltraCluster by combining 4,000 or more GPUs. These will provide businesses with access to supercomputer-scale machine learning and high-performance computing solutions, including financial modelling, natural language processing and other forms of deep analysis.

Regardless of the size of an organization, the new P4d instances should help businesses solve their biggest machine learning challenges while significantly lowering costs. Productivity benefits are also promised with multi-node distributed training taking less time and more managed services being made available.

With machine learning becoming increasingly prevalent across industries, a broad spectrum of businesses is likely to be interested in AWS’ new GPU-instances, whether they have used the company’s previous instances or not.

AWS announced on Monday, the launch of next-generation GPU equipped EC2 P4 instances for machine learning and high performance computing. These instances will be powered by NVIDIA’s new A100 tensor core GPUs and Intel Cascade Lake processors.

Amazon Web Services (AWS) launched its first-generation Cluster GPU instances back in 2010, and the previous gen was launched in 2019. According to AWS, the upgraded P4 Cluster GPU instances can deliver up to 2.5x the deep learning performance, and up to 60% lower cost to train when compared to P3 (previous-gen) instances.

The due upgrade comes after NVIDIA launched its next-generation GPUs this year which took the computer industry by storm. The release included the RTX 3000 series GPUs for personal computers and ampere architecture based data center GPUs for AI, data analytics, and high-performance computing (HPC).

Each cluster will be powered by an Intel Cascade Lake CPU and 8 A100 NVIDIA tensor core GPUs connected with NVLink and support GPUDirect. These instances offer 2.5 PetaFLOPS of floating point performance and 320 GB of high-bandwidth GPU memory. They include 1.1 TB of system memory and 8 TB of NVME-based SSD storage that can deliver up to 16 gigabytes of read throughput per second. According to AWS, the customer gets access to 100 Gbps network connections to a dedicated network designed specifically for P4, along with 19 Gbps of EBS bandwidth that can support up to 80K IOPS.

Currently, the Cluster GPU instances are only available in one size: p4d.24xlarge, which includes 1 CPU and 8 A100 GPUs. They are available in US East (Northern Virginia) and US West (Oregon) regions.

AWS also announced the ultra-powerful EC2 UltraClusters, which comes with 4,000 or more A100 GPUs. This is an AWS ParallelCluster, which is mostly targeted for large businesses and corporations. “These clusters can take on your toughest supercomputer-scale machine learning and HPC workloads: natural language processing, object detection & classification, scene understanding, seismic analysis, weather forecasting, financial modeling, and so forth,” wrote Amazon, in P4 press release.

The market for machine learning and AI is rapidly growing and expanding, and some experts even go as far as to say that AI is the future of technology. On the other hand, with the growth in size of available data, data processing tasks are becoming more and more power hungry. With AWS Cluster GPU instances powered by the latest GPUs and CPUs built for data centers, customers can remotely harness all the power they require to train their AI models or to process and analyze large amounts of data without having to invest in the hardware themselves.