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PNY Pushes Storage Evolution with New Blisteringly Fast, Low-cost Flash Arrays for NVDIA GPU Servers
PNY Technologies has launched a new range of AI storage appliances, redeveloped by PEAKAIO to deliver unseen price to performance ratios to suit the emerged A.I. market which is seeing increasing numbers of smaller clusters of GPU servers.
The NVIDIA DGX A100 supercomputer has provided organisations and research institutions with a new capability, and as these projects have grown, so have the number of smaller clusters of NVIDIA DGX’s. Which in turn places even more demand on the storage system.
While many storage vendors have raced to develop solutions for multi petabyte super-pods, PNY has focused on a solution for the average customer. Engaging with a Software Defined Storage team to develop a PNY bespoke solution focused purely on NVIDIA key features, such as HDR/200Gbe and GPUDirect, yet starting at 30TB. The solutions are designed to be affordable for new projects, while still delivering full HDR/200Gbe performance. The 1U is expandable to 150TB and the 2U 360TB, with optional 1U / 2U expansion boxes should projects scale.
The 1U has been aimed at the growing POD / Edge market where ultra-fast storage is required for inferencing, but cost and space are critical.
The A.I. market has not scaled as some expected and has not followed the HPC pattern where clusters of servers scale dramatically, which in turn requires large parallel storage solutions. Instead, we have seen 90% plus of projects scale to small clusters, for example five DGX servers, and then break out to form multiple smaller clusters or edge-based solutions. This is a key difference with GPU based workflows and a testimony to the power of the NVIDIA GPUs. However, it has highlighted a real gap in the current storage market, the generation 2 PNY 3S-Storage solutions have been designed to perfectly bridge this gap.
Project funds are best spent on GPUs, it is these GPUs which provide the user value and ROI. Yet we need to ensure that the storage can keep the GPUs active and offer the quality to sustain such high levels of performance. Our generation 1 solution provided this, but with NVMe-oF as the only connectivity, it was mostly restricted to single servers. As projects grew, even if only two servers, they needed more storage power and the ability to share data. This was the challenge and took considerable focus, investment and time, but the results we believe will change what a default A.I. POD solution looks like. If you are starting an A.I. project and need to factor in storage while ensuring your funds are mostly spent on GPU, this provides a simple, plug-n-play appliance solution.
The solution is currently unique to PNY and although their primary focus is price, performance and ease of use, recognising the growing challenges faced by isolated and edge-based solutions, additional features are being developed to help unify the complete NVIDIA POD, for example, full NVIDIA monitoring; not only will the PNY storage monitor itself, but it will also monitor the NVIDIA DGX and Mellanox switch creating a single unified support path for solution partners to provide full remote monitoring.
“PNY aim to provide partners with all the elements needed to create a full solution, adding unified NVIDIA POD remote monitoring options is just an extension of PNY’s commitment to helping resellers deliver solutions”.
“Clearly the focus on performance has paid off. In our tests, even an entry level 1U solution outperformed an enterprise class all flash array. In storage, we have many test methods to provide great benchmark results, commonly we will use multiple servers to drive the storage faster and achieve good-looking and marketable performance figures. However, with the PNY solutions, a single NVIDIA A100 server could easily saturate the HDR/200Gbe link. Put simply, it outperformed most leading vendors at a fraction of the cost, without even trying hard”
“Running real-life deep learning tests, we simply could not throw enough hardware at it, we had three DGX servers fully maxed out and the storage looking like it was hardly trying. The new design has made good use of the NVIDIA Mellanox RDMA strengths, building a new storage stack to take full advantage of its ultra-low latency and high bandwidth. But, ultimately, I was most impressed with its ease, we simply plugged it in and within minutes we were up and flying”