Direct IO Performance Using Nvidia GPUDirect Storage  

By Doug Eadline

August 2, 2023

The focus on GPU processing speeds makes sense. The massive uplift in processing has been important in many areas including HPC and now Generative AI with LLM (Large Language Models). While performance is important, the other aspect of GPU computing is direct storage. 

Like Nvidia GPUDirect communications (GPU-GPU communication), GPUDirect Storage (GDS) is an NVMe and CPU-bypass protocol to enable storage systems to rapidly send and receive data to storage devices without involving the host processor.  

GPUDirect storage avoids extra data copying required when data passes through the CPU. It enables a direct memory access (DMA) engine near the NIC or storage to move data on a direct path into or out of GPU memory — all without CPU overhead (and data copies).

GPUDirect Storage by the Numbers

Recently, an article at Blocks and Files provided some publicly available performance numbers for various storage platforms and GPUDirect Storage.  

Dell, DDN, IBM, NetApp (ONTAP and E-Series BeeGFS), Pure Storage, VAST Data and WekaIO all report GPUDirect Storage capabilities. Of course, you do not need GPUDirect Storage to read and write data from GPU memory, but if you want to move data as fast as possible between GPUs and storage platforms, going “direct” is your best option. 

Blocks and Files (B&F) collected all the sequential read and write storage node bandwidth numbers that we could find for Dell, DDN, IBM, NetApp, Pure and VAST Data systems when using GPUDirect storage.

Note B&F could not find sequential WekaIO numbers, so they were not included in the results. The following chart depicts the results. 

Nvidia Direct Storage chart
Source: https://blocksandfiles.com/2023/07/31/storage-system-speed-serving-data-to-nvidia-gpus

The clear winner was DDN with 90 GBps of read bandwidth and 65 GBps write bandwidth. In terms of read Bandwidth VAST was second, followed by IBM ESS3200, with NetApp E series in fourth, ONTAP in fifth place and Dell in last place. 

The write results were quite different, with IBM coming in second, NetApp E series in third, VAST in fourth, Pure in fifth, NetApp ONTAP in sixth and Dell in last place. 

The raw data and more system details are available in the Blocks and Files article. Aside from the performance data, there are a few takeaways from this comparison. First, fast read performance does not always guarantee fast write performance (and vise-versa). And second, providing a capability (to a specific specification) does not imply efficient performance. In all cases the GPUDirect storage worked, but only DDN has delivered on both fast read and write performance. The other vendors in the survey will certainly be looking to improve their performance in the near future.  

 

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