XR4000: Don’t be Afraid of the Edge!
Tue, 06 Dec 2022 23:18:48 -0000
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Halloween is just around the corner, and we have been seeing all sorts of innovative decorations around our neighborhood. The malls and shops are filled with cool gadgets to get the best scare out of you. Well, everything is getting an upgrade with technology, so why not Halloween? Are you trying to set up the haunted house you always wanted? AR apps are a must-try for that! Need a dancing skeleton, friendly ghost Casper, or maybe just the fanciest costume for your dog? Everything is possible with the help of an edge computing solution. Bringing the processing and computing of a data center to the edge and reducing latency to a minimum enables myriad use cases for retail and manufacturing.
Dell Technologies’ latest PowerEdge server, Dell PowerEdge XR4000, powered by Intel Xeon-D HCC 2700 SoC, comes in a unique sled and chassis form factor. One of the best values of this server is the short depth of just 355 mm (with bezel) (see PowerEdge XR4000—Small But Mighty), which enables you to put this server in a shoebox or mount it on a closet wall and forget about it. The sled comes in 1U and 2U form factors, which enables various deployment options depending on the edge workload. It is purpose-built for rugged conditions and can operate in a temperature range of –5°C to 55°C. So whether you are in Texas or California, XR4000 will continue to perform reliably. No need to worry about dust storms, tornadoes, or hail because this edge server has industry-standard certification for NEBS and MIL-STD.
PowerEdge XR4000 is powered by Intel Xeon D (Ice Lake D), making it Dell’s first Xeon D-based server. This ”made-for-the-edge” CPU comes with up to 20 cores with support of extended temperatures. It is up to 2.97x faster than its previous generation Skylake-D. The AI inferencing (CPU) gains have been improved by up to 7.4x. Ethernet connectivity is up by 400%, by providing networking up to 100 GbE and a variety of port options, with up to eight ports at 25, 10, or 1 Gbps with RDMA (iWARP and RoCEv2). Ethernet processing throughput is up by 150%, with 50 Gbps and 100 Gbps throughput options.
Support for NVIDIA A2 and A30 GPUs also enables smooth operation for AI/ML workloads. We ran industry-standard MLPerf 2.0 for ssd-resnet34 (object detection, large) workload testing on XR4000 with 1 x A2 GPU and concluded that it has 11% lower latency (in milliseconds) than a 1 x A2 GPU configuration of Supermicro SYS-220HE for multi-stream scenario.[1a] This means that XR4000 can analyze frames from multiple cameras simultaneously 11% faster than Supermicro.[1b] So, Halloween need not be limited to just the scary gadgets; we can also ensure the security in our neighborhood by real-time tracking of our streets and live video streams, making sure that no suspicious activity is taking place around the block. XR4000 also has 12% more throughput (in samples/second) than Supermicro SYS-220HE in ssd-resnet34 (object detection, small) offline scenario [2a] (one of the most used real-life scenarios). This means if you don’t have a constant flow of data, and instead have it all in the memory, XR4000 can identify the people and locations in a photo album much faster.[2b] The offline scenario represents batch-processing applications where all data is immediately available and latency is unconstrained.
One of my favorite Halloween characters is Hermione, so how can we leave a Harry Potter-themed party out of the picture? The “Sorting Hat” is the magical AI that can recognize and assign the Hogwarts house, but with the XR4000 using BERT NLP, we can truly offer real-life AI that delivers better outcomes and lower latency. If you want to test your knowledge of Harry Potter trivia, use AI’s help to get the right answers immediately. The secret sauce here would be using a natural language processing (NLP) tool called BERT (Bidirectional Encoder Representations from Transformers). Before BERT, NLP was unidirectional, which means the algorithm could only understand text read in one direction. BERT understands text in both directions, so it’s easy for it to get full context with just a word. We ran a similar workload on XR4000 using MLPerf 2.0 called bert-99 (Lang Processing) with an A2 GPU. It resulted in 11% lower latency than the Supermicro SYS-220HE (lower is better). [3a,b]
So far, Halloween is looking great with XR4000, but that’s not it. We can add more features pertaining to the safety of the kids. For example, parents can choose to witness their children during trick or treating without getting in the way of the fun—in the same way XR4000 with its optional Nano server sled can provide an in-chassis witness node for a vSAN cluster. Replacing the need for a virtual witness node, the Nano server can function as an in-chassis witness node, allowing for a native, self-contained 2-node vSAN cluster in even the 14” x 12” stackable server chassis. This allows for VM deployments where the option was previously out of the question due to latency or bandwidth constraints, and, ultimately, we can just come up with a virtual trick-or-treat app! A single-socket Dell PowerEdge XR4000 server equipped with the Intel Xeon D-2776NT has a VMmark Power Performance score of 3.64 @ 4 Tiles.[4] This is representative of different virtualization workloads that can run optimally maintaining the constraints of latency important for the edge with a strong level of performance while keeping power measurement in check, making it an excellent choice for edge customers who want to take advantage of the benefits that virtualization has to offer.
All these use cases are in the category of edge computing. Compute and storage resources are placed closer to where data is collected, processed, and consumed, eliminating the backhaul latency that occurs when sending/receiving data from a traditional data center. On top of all this, system management provides options so you don’t need to worry about maintenance issues or missing a data point or trends because at the heart of PowerEdge XR4000 is the integrated Dell Remote Access Controller 9 (iDRAC9). It is embedded in the server to streamline the process of deployment, update, service, and troubleshooting—all remotely or from your cellphone app.
It’s safe to say that the edge does not scare us anymore! PowerEdge XR4000 is a unique short-depth edge server that helps with low power and low footprint, and ultimately lowers TCO.
To learn more about the PowerEdge XR4000, see PowerEdge XR Rugged Servers.
Reference
[1a] Unverified MLPerf v2.0 Inference ssd-resnet34 (object detection, large), multistream. Result not verified by MLCommons Association. MLPerf name and logo are trademarks of MLCommons Association in the United States and other countries. All rights reserved. Unauthorized use strictly prohibited. See www.mlcommons.org for more information.
[1b] Based on testing conducted in Dell Cloud and Emerging Technology lab. For a multistream video, XR4000 has 11% less latency than Supermicro SYS-220HE for object detection (large workload).
[2a] Unverified MLPerf v2.0 Inference ssd-resnet34 (object detection, small), offline. Result not verified by MLCommons Association. MLPerf name and logo are trademarks of MLCommons Association in the United States and other countries. All rights reserved. Unauthorized use strictly prohibited. See www.mlcommons.org for more information.
[2b] Based on testing conducted in Dell Cloud and Emerging Technology lab, For an offline scenario, XR4000 has 12% more throughput than Supermicro SYS-220HE for object detection (small workload).
[3a] Unverified MLPerf v2.0 Inference bert-99 (Lang Processing). Result not verified by MLCommons Association. MLPerf name and logo are trademarks of MLCommons Association in the United States and other countries. All rights reserved. Unauthorized use strictly prohibited. See www.mlcommons.org for more information.
[3b] Based on testing conducted in Dell Cloud and Emerging Technology lab, For a single-stream video, XR4000 has 11% lower latency than Supermicro SYS-220HE for language processing task.
[4] Based on the performance testing conducted in Dell Solution Performance Analysis (SPA) lab on 9/30/2022.