{"id":52463,"date":"2023-03-06T08:00:26","date_gmt":"2023-03-06T16:00:26","guid":{"rendered":"https:\/\/phisonblog.com\/?p=52463"},"modified":"2025-07-21T17:06:51","modified_gmt":"2025-07-22T00:06:51","slug":"how-enterprise-storage-networking-is-evolving","status":"publish","type":"post","link":"https:\/\/phisonblog.com\/de\/how-enterprise-storage-networking-is-evolving\/","title":{"rendered":"Wie sich Enterprise Storage Networking weiterentwickelt"},"content":{"rendered":"

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Networking has been a critical component of data centers since the beginning. How the system connects resources across the enterprise ecosystem makes a big difference in how efficient and effective the system is.<\/p>\n

Over the past 10 years or so, enterprise data centers have been evolving rapidly in response to a number of technological advances, such as the cloud, edge computing, containerization, cloud-native computing and so on. To stay competitive, organizations need to deploy smart and flexible storage architectures that are highly automated and capable of moving data through the entire system efficiently and quickly.<\/p>\n

In this article, we\u2019ll take a look at two specific factors that are driving the rapid evolution of data center storage<\/a> networking:<\/p>\n

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Read: Technology Advances in Data Storage<\/div><\/div><\/div><\/div><\/div>\n

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Compute Express Link (CXL)<\/h3>\n

CXL<\/a> is an open standard cache-coherent interconnect that links memory to processing tasks in servers and storage. It builds on the already-fast PCI Express (PCIe) interconnect, which has been a standard for some time now.<\/p>\n

The latest PCIe iteration, Gen5, can potentially connect CPUs and peripherals at speeds up to 32 gigatransfers per second (GT\/s). PCIe has some limitations, however, that hinder data access speeds today. One of those limitations is that it doesn\u2019t manage separated stores of memory very efficiently. Another is that the latency of PCIe is too high to efficiently share memory across several devices.<\/p>\n

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Consider this: many of today\u2019s servers, especially those of hyperscalers, contain components that come with their own on-board memory. Besides the main memory attached to a host processor, there also might be smart NICs, GPUs and storage SSDs. These devices have memory caches that often are underutilized, some by a lot. That means that throughout that system, there is a lot of memory lying idle. Multiply all that unused memory by thousands of servers and it becomes significant. These caches typically can\u2019t interact unless they have a tool to connect them.<\/p>\n

CXL overcomes these limitations. Developed partly to address the inability of storage-class memory to adequately handle numerous processing nodes, CXL utilizes the physical connection layer and electrical configuration of PCIe but has much lower latency when accessing data from memory. It provides cache coherency between host servers and other devices, so memory across the entire system is treated as a single accessible pool. These memory pools can significantly increase capacity and can link directly to CPU and GPU processors, as well as computational storage and intelligent network interface cards (NICs).<\/p>\n

With CXL-compatible systems just now beginning to launch, the technology has the potential to transform how platforms and data centers are designed and run. The industry will gradually shift away from the concept of each node having its own memory and processing\u2014in favor of disaggregated infrastructure that assigns resources to workloads from a large single pool of memory that serves the entire ecosystem, including any number of GPUs, CPUs and computational storage. That allows organizations to build data centers with capacities of massive volumes of memory.<\/p>\n

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Read: How Data Growth Impacts Enterprise Storage<\/div><\/div><\/div><\/div><\/div>\n

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Benefits of CXL<\/h3>\n

With CXL, organizations are no longer confined to proprietary interconnects between storage, compute, memory and storage-class memory\u2014so multiple processors are able to share bigger pools of memory than they could before.<\/p>\n

CXL also enables organizations to achieve greater capacity and bandwidth beyond DRAM. Using a CXL-attached device, they can add memory to a CPU or GPU host processor. That means the CPU and GPU could have access to terabytes of storage at DRAM speed.<\/p>\n

While the latency of storage vs. DRAM isn\u2019t really comparable (say, 80 microseconds to .25 microsecond respectively), there\u2019s still no real need to move everything into DRAM. Using CXL, the system can fetch the data it needs from the SSD through the existing memory hierarchy built into the CPU\u2014meaning there\u2019s no need for a file system and all the accompanying layers, which can add 10 to 20 microseconds of latency.<\/p>\n

File systems aren\u2019t going away anytime soon, of course, because they serve a valuable purpose for general computing. But through CXL, organizations can create pools of SSD storage data that augment compute capabilities at a fraction of the cost of DRAM. So now, instead of being limited to a dataset that fits into 128 GB of DRAM, organizations can have hundreds of TBs of NVMe SSD storage running at PCIe Gen6 speeds.<\/p>\n

Other benefits of CXL include:<\/p>\n