RDMA – NVIDIA Technical Blog News and tutorials for developers, data scientists, and IT admins 2025-07-08T01:00:00Z http://www.open-lab.net/blog/feed/ Tim Lustig <![CDATA[Spotlight: NVIDIA BlueField DPUs Power the VAST Data Platform for AI Workload Optimization]]> http://www.open-lab.net/blog/?p=85204 2024-10-11T20:02:14Z 2024-08-06T18:00:00Z As the demand for sophisticated AI capabilities escalates, VAST Data introduces the VAST Data Platform, now enhanced with NVIDIA BlueField DPUs. This innovation...]]> As the demand for sophisticated AI capabilities escalates, VAST Data introduces the VAST Data Platform, now enhanced with NVIDIA BlueField DPUs. This innovation...

As the demand for sophisticated AI capabilities escalates, VAST Data introduces the VAST Data Platform, now enhanced with NVIDIA BlueField DPUs. This innovation is tailored to meet the stringent demands of AI-driven data centers and optimize AI workloads and data management. This post presents how BlueField DPUs provide VAST with a significant boost in both performance and efficiency to��

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Elena Agostini <![CDATA[Unlocking GPU-Accelerated RDMA with NVIDIA DOCA GPUNetIO]]> http://www.open-lab.net/blog/?p=83998 2024-06-27T23:59:16Z 2024-06-13T20:43:59Z NVIDIA DOCA GPUNetIO is a library within the NVIDIA DOCA SDK, specifically designed for real-time inline GPU packet processing. It combines technologies like...]]> NVIDIA DOCA GPUNetIO is a library within the NVIDIA DOCA SDK, specifically designed for real-time inline GPU packet processing. It combines technologies like...

NVIDIA DOCA GPUNetIO is a library within the NVIDIA DOCA SDK, specifically designed for real-time inline GPU packet processing. It combines technologies like GPUDirect RDMA and GPUDirect Async to enable the creation of GPU-centric applications where a CUDA kernel can directly communicate with the network interface card (NIC) for sending and receiving packets, bypassing the CPU and excluding it��

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Aviv Barnea <![CDATA[Scaling Zero Touch RoCE Technology with Round Trip Time Congestion Control]]> http://www.open-lab.net/blog/?p=41691 2022-08-21T23:53:09Z 2021-12-14T22:10:52Z NVIDIA Zero Touch RoCE (ZTR) enables data centers to seamlessly deploy RDMA over Converged Ethernet (RoCE) without requiring any special switch configuration....]]> NVIDIA Zero Touch RoCE (ZTR) enables data centers to seamlessly deploy RDMA over Converged Ethernet (RoCE) without requiring any special switch configuration....Zero Touch RoCE enables a smooth data highway

NVIDIA Zero Touch RoCE (ZTR) enables data centers to seamlessly deploy RDMA over Converged Ethernet (RoCE) without requiring any special switch configuration. Until recently, ZTR was optimal for only small to medium-sized data centers. Meanwhile, large-scale deployments have traditionally relied on Explicit Congestion Notification (ECN) to enable RoCE network transport��

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Motti Beck <![CDATA[VxRail Boosts Application Performance Using vSAN RDMA]]> http://www.open-lab.net/blog/?p=38154 2022-08-21T23:52:47Z 2021-10-05T12:00:00Z Hybrid cloud refers to a mix of computing and storage services of on-premises infrastructure, like Dell EMC VxRail hyperconverged infrastructure (HCI) and...]]> Hybrid cloud refers to a mix of computing and storage services of on-premises infrastructure, like Dell EMC VxRail hyperconverged infrastructure (HCI) and...Block diagram of vSphere clusters with virtual servers, NICs and and management interface

Hybrid cloud refers to a mix of computing and storage services of on-premises infrastructure, like Dell EMC VxRail hyperconverged infrastructure (HCI) and multipublic cloud services such as Amazon Web Services or Microsoft Azure. Hybrid cloud architecture gives you the flexibility to maintain traditional IT on-premises deployments for running business-critical applications or to protect sensitive��

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Christian Hundt <![CDATA[Machine Learning Frameworks Interoperability, Part 2: Data Loading and Data Transfer Bottlenecks]]> http://www.open-lab.net/blog/?p=35948 2022-08-21T23:52:27Z 2021-08-17T16:30:00Z Efficient pipeline design is crucial for data scientists. When composing complex end-to-end workflows, you may choose from a wide variety of building blocks,...]]> Efficient pipeline design is crucial for data scientists. When composing complex end-to-end workflows, you may choose from a wide variety of building blocks,...

Efficient pipeline design is crucial for data scientists. When composing complex end-to-end workflows, you may choose from a wide variety of building blocks, each of them specialized for a dedicated task. Unfortunately, repeatedly converting between data formats is an error-prone and performance-degrading endeavor. Let��s change that! In this post series, we discuss different aspects of��

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Motti Beck <![CDATA[Doubling Network File System Performance with RDMA-Enabled Networking]]> http://www.open-lab.net/blog/?p=24842 2023-07-05T19:33:10Z 2021-03-29T23:36:13Z [stextbox id="info"]This post was originally published on the Mellanox blog.[/stextbox] Network File System (NFS) is a ubiquitous component of most modern...]]> [stextbox id="info"]This post was originally published on the Mellanox blog.[/stextbox] Network File System (NFS) is a ubiquitous component of most modern...

This post was originally published on the Mellanox blog. Network File System (NFS) is a ubiquitous component of most modern clusters. It was initially designed as a work-group filesystem, making a central file store available to and shared among several client servers. As NFS became more popular, it was used for mission-critical applications, which required access to storage. Next��

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Ash Bhalgat https://www.linkedin.com/in/ashbhalgat/ <![CDATA[Scaling Out the Deep Learning Cloud Efficiently]]> http://www.open-lab.net/blog/?p=23392 2022-08-21T23:40:59Z 2021-01-22T22:30:59Z The Duchess of Windsor famously said that you can never be too rich or too thin. A similar observation is true when trying to match deep learning applications...]]> The Duchess of Windsor famously said that you can never be too rich or too thin. A similar observation is true when trying to match deep learning applications...

The Duchess of Windsor famously said that you can never be too rich or too thin. A similar observation is true when trying to match deep learning applications and compute resources: You can never have too much horsepower. Intractable problems in fields as diverse as finance, security, medical research, resource exploration, self-driving vehicles, and defense are being solved today by training��

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CJ Newburn <![CDATA[Accelerating IO in the Modern Data Center: Network IO]]> http://www.open-lab.net/blog/?p=21733 2022-08-21T23:40:44Z 2020-10-20T19:13:11Z This is the second post in the Accelerating IO series, which describes the architecture, components, and benefits of Magnum IO, the IO subsystem of the modern...]]> This is the second post in the Accelerating IO series, which describes the architecture, components, and benefits of Magnum IO, the IO subsystem of the modern...

This is the second post in the Accelerating IO series, which describes the architecture, components, and benefits of Magnum IO, the IO subsystem of the modern data center. The first post in this series introduced the Magnum IO architecture and positioned it in the broader context of CUDA, CUDA-X, and vertical application domains. Of the four major components of the architecture��

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CJ Newburn <![CDATA[Accelerating IO in the Modern Data Center: Magnum IO Architecture]]> http://www.open-lab.net/blog/?p=21121 2023-03-22T01:09:09Z 2020-10-05T13:00:00Z This is the first post in the Accelerating IO series, which describes the architecture, components, storage, and benefits of Magnum IO, the IO subsystem of the...]]> This is the first post in the Accelerating IO series, which describes the architecture, components, storage, and benefits of Magnum IO, the IO subsystem of the...

This is the first post in the Accelerating IO series, which describes the architecture, components, storage, and benefits of Magnum IO, the IO subsystem of the modern data center. Previously the boundary of the unit of computing, sheet metal no longer constrains the resources that can be applied to a single problem or the data set that can be housed. The new unit is the data center.

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Ashok Kelur <![CDATA[GPUDirect RDMA on NVIDIA Jetson AGX Xavier]]> http://www.open-lab.net/blog/?p=14675 2023-02-13T17:45:44Z 2019-06-11T13:00:25Z Remote Direct Memory Access (RDMA) allows computers to exchange data in memory without the involvement of a CPU. The benefits include low latency and high...]]> Remote Direct Memory Access (RDMA) allows computers to exchange data in memory without the involvement of a CPU. The benefits include low latency and high...

Remote Direct Memory Access (RDMA) allows computers to exchange data in memory without the involvement of a CPU. The benefits include low latency and high bandwidth data exchange. GPUDirect RDMA extends the same philosophy to the GPU and the connected peripherals in Jetson AGX Xavier. GPUDirect RDMA enables a direct path for data exchange between the GPU-accessible memory (the CUDA memory) and a��

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Davide Rossetti <![CDATA[Benchmarking GPUDirect RDMA on Modern Server Platforms]]> http://www.open-lab.net/blog/parallelforall/?p=3451 2023-07-05T19:44:19Z 2014-10-08T02:27:45Z NVIDIA GPUDirect RDMA is a technology which enables a direct path for data exchange between the GPU and third-party peer devices using standard features of PCI...]]> NVIDIA GPUDirect RDMA is a technology which enables a direct path for data exchange between the GPU and third-party peer devices using standard features of PCI...

NVIDIA GPUDirect RDMA is a technology which enables a direct path for data exchange between the GPU and third-party peer devices using standard features of PCI Express. Examples of third-party devices include network interfaces, video acquisition devices, storage adapters, and medical equipment. Enabled on Tesla and Quadro-class GPUs, GPUDirect RDMA relies on the ability of NVIDIA GPUs to expose��

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