This post was updated May 8, 2023. A growing number of network applications need to exercise GPU real-time packet processing in order to implement high data rate solutions: data filtering, data placement, network analysis, sensors�� signal processing, and more. One primary motivation is the high degree of parallelism that the GPU can enable to process in parallel multiple packets while��
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Cloud computing is designed to be agile and resilient to deliver additional value for businesses. China Mobile (CMCC), one of China��s largest telecom operators and cloud services providers, offers precisely this with its Bigcloud public cloud offering. Bigcloud provides PaaS and SaaS services tailored to the needs of enterprise cloud and hybrid-cloud solutions for mission-critical��
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The inline processing of network packets using GPUs is a packet-analysis technique useful to a number of different application domains: signal processing, network security, information gathering, input reconstruction, and so on. The main requirement of these application types is to move received packets into GPU memory as soon as possible, to trigger the CUDA kernel responsible to execute��
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The NVIDIA BlueField DPU (data processing unit) can be used for network function acceleration. This network offloading is possible using DPDK and the NVIDIA DOCA software framework. In this series, I built an app and offloaded it two ways, through the use of DPDK and the NVIDIA DOCA SDK libraries. I recorded each step as a separate code patch and provided the complete steps in each series.
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This post was originally published on the Mellanox blog. In the first post of this series, I argued that it is a function and not a form that distinguishes a SmartNIC from a data processing unit (DPU). I introduced the category of datacenter NICs called SmartNICs, which include both hardware transport and a programmable data path for virtual switch acceleration.
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DOCA is a software framework for developing applications on BlueField DPUs. By using DOCA, you can offload infrastructure workloads from the host CPU and accelerate them with the BlueField DPU. This enables an infrastructure that is software-defined yet hardware accelerated, maximizing both performance and flexibility in the data center. NVIDIA first introduced DOCA in October 2020.
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This post was originally published on the Mellanox blog. In part one, I said that the smart devices around us are changing our lives in remarkable ways. However, the infrastructure to support these smart innovations hasn��t fully evolved in terms of flexibility, performance, and efficiency. A software-defined world offers flexibility but at the cost of performance and efficiency.
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Today, in his NVIDIA GTC Fall keynote, CEO Jensen Huang introduced a new kind of processor, the BlueField-2 data processing unit (DPU), a powerful new software development kit for the DPU, DOCA, along with a three year roadmap of DPU and AI innovation. The NVIDIA BlueField-2 DPU is the world��s first data center infrastructure on a chip architecture optimized for modern enterprise data centers.
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This post was originally published on the Mellanox blog. At Red Hat Summit 2018, NVIDIA Mellanox announced an open network functions virtualization infrastructure (NFVI) and cloud data center solution. The solution combined Red Hat Enterprise Linux cloud software with in-box support of NVIDIA Mellanox NIC hardware. Our close collaboration and joint validation with Red Hat yielded a fully��
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