Topic

DOCA GPUNetIO

1 post about DOCA GPUNetIO. Every summary links to the original.

Paid picks we use ourselves. Links carry a referral code — a subscription through one earns us a commission at no extra cost to you.

Newest first

Posts

NVIDIA
How DOCA GPUNetIO Unifies GPU-Initiated Networking Across the NVIDIA Software Stack
NVIDIA DOCA GPUNetIO is a GPU-centric networking SDK that enables CUDA kernels to drive Ethernet, RDMA, Verbs, and DMA operations with the CPU removed from the application critical path. It unifies previously fragmented GDA-KI-style RDMA implementations from libraries such as NCCL, NVSHMEM, UCX, and the Aerial 5G SDK into a single shared foundation. The framework provides both a full DOCA SDK version and a lighter open-source Verbs-focused implementation; the open-source version can optionally dlopen the SDK at runtime. On the data path, CUDA kernels directly post Work Queue Entries, ring the NIC doorbell, and poll for completions without CPU intervention. Benchmarks using NVSHMEM show that the GPU-initiated path avoids the CPU proxy bottleneck, achieving higher bandwidth for small message sizes compared to CPU-mediated communication.

The best engineering reads, once a week.

Topic

1 post about DOCA GPUNetIO. Every summary links to the original.

Paid picks we use ourselves. Links carry a referral code — a subscription through one earns us a commission at no extra cost to you.

Newest first

NVIDIA
How DOCA GPUNetIO Unifies GPU-Initiated Networking Across the NVIDIA Software Stack
NVIDIA DOCA GPUNetIO is a GPU-centric networking SDK that enables CUDA kernels to drive Ethernet, RDMA, Verbs, and DMA operations with the CPU removed from the application critical path. It unifies previously fragmented GDA-KI-style RDMA implementations from libraries such as NCCL, NVSHMEM, UCX, and the Aerial 5G SDK into a single shared foundation. The framework provides both a full DOCA SDK version and a lighter open-source Verbs-focused implementation; the open-source version can optionally dlopen the SDK at runtime. On the data path, CUDA kernels directly post Work Queue Entries, ring the NIC doorbell, and poll for completions without CPU intervention. Benchmarks using NVSHMEM show that the GPU-initiated path avoids the CPU proxy bottleneck, achieving higher bandwidth for small message sizes compared to CPU-mediated communication.

The best engineering reads, once a week.