Posts Tagged 'data centers'
-
May 21, 2025
Auto-Load Balancing and Teralynx 10: Optimizing Cloud and AI Infrastructure
By Kishore Atreya, Senior Director of Cloud Platform Marketing, Marvell
Milliseconds matter.
It’s one of the fundamental laws of AI and cloud computing. Reducing the time required to run an individual workload frees up infrastructure to perform more work, which in turn creates an opportunity for cloud operators to potentially generate more revenue. Because they perform billions of simultaneous operations and operate on a 24/7/365 basis, time literally is money to cloud operators.
Marvell specifically designed the Marvell® Teralynx® 10 switch to optimize infrastructure for the intense performance demands of the cloud and AI era. Benchmark tests show that Teralynx 10 operates at a low and predictable 500 nanoseconds, a critical precursor for reducing time-to-completion.1 The 512-radix design of Teralynx 10 also means that large clusters or data centers with networks built around the device (versus 256-radix switch silicon) need up to 40% fewer switches, 33% fewer networking layers and 40% fewer connections to provide an equivalent level of aggregate bandwidth.2 Less equipment, of course, paves the way for lower costs, lower energy and better use of real estate.
Recently, we also teamed up with Keysight to provide deeper detail on another crucial feature of critical importance: auto-load balancing (ALB), or the ability of Teralynx 10 to even out traffic between ports based on current and anticipated loads. Like a highway system, spreading traffic more evenly across lanes in networks prevents congestion and reduces cumulative travel time. Without it, a crisis in one location becomes a problem for the entire system.
Better Load Balancing, Better Traffic Flow
To test our hypothesis of utilizing smarter load balancing for better load distribution, we created a scenario with Keysight AI Data Center Builder (KAI DC Builder) to measure port utilization and job completion time across different AI collective workloads. Built around a spine-leaf topology with four nodes, KAI DC Builder supports a range of collective algorithms, including all-to-all, all-reduce, all-gather, reduce-scatter, and gather. It facilitates the generation of RDMA traffic and operates using the RoCEv2 protocol. (In lay person’s terms, KAI DC Builder along with Keysight’s AresONE-M 800GE hardware platform enabled us to create a spectrum of test tracks.)
For generating AI traffic workloads, we used the Keysight Collective Communication Benchmark (KCCB) application. This application is installed as a container on the server, along with the Keysight provided supportive dockers..
In our tests, Keysight AresONE-M 800GE was connected to a Teralynx 10 Top-of-Rack switch via 16 400G OSFP ports. The ToR switch in turn was linked to a Teralynx 10 system configured as a leaf switch. We then measured port utilization and time-of-completion. All Teralynx 10 systems were loaded with SONiC.
-
April 17, 2025
Five Ways CXL Will Transform Computing
By Michael Kanellos, Head of Influencer Relations, Marvell
This story was also featured in Electronic Design
Some technologies experience stunning breakthroughs every year. In memory, it can be decades between major milestones. Burroughs invented magnetic memory in 1952 so ENIAC wouldn’t lose time pulling data from punch cards1. In the 1970s DRAM replaced magnetic memory while in the 2010s, HBM arrived.
Compute Express Link (CXL) represents the next big step forward. CXL devices essentially take advantage of available PCIe interfaces to open an additional conduit that complements the overtaxed memory bus. More lanes, more data movement, more performance.
Additionally, and arguably more importantly, CXL will change how data centers are built, operate and work. It’s a technology that will have a ripple effect. Here are a few scenarios on how it can potentially impact infrastructure:
1. DLRM Gets Faster and More Efficient
Memory bandwidth—the amount of memory that can be transmitted from memory to a processor per second—has chronically been a bottleneck because processor performance increases far faster and more predictably than bus speed or bus capacity. To help contain that gap, designers have added more lanes or added co-processors.
Marvell® StructeraTM A does both. The first-of-its-kind device in a new industry category of memory accelerators, Structera A sports 16 Arm Neoverse N2 cores, 200 Gbps of memory bandwidth, up to 4TB of memory and consumes under 100 watts along with processing fabric and other Marvell-only technology. It’s essentially a server-within-a-server with outsized memory bandwidth for bandwidth-intensive tasks like inference or deep learning recommendation models (DRLM). Cloud providers need to program their software to offload tasks to Structera A, but doing so brings a number of benefits.
Take a high-end x86 processor. Today it might sport 64 cores, 400 Gbps of memory bandwidth, up to 2TB of memory (i.e. four top-of-the-line 512GB DIMMs), and consume a maximum 400 watts for a data transmission power rate 1W per GB/sec.
-
March 24, 2025
In AI, The Voyage from Bigger to Better Is Underway
By Michael Kanellos, Head of Influencer Relations, Marvell
Bigger is better, right? Look at AI: the story swirls with superlatives.
ChatGPT landed one million users within five days,1 far surpassing the pace of any previous technology. The compute requirements of training notable AI models increases 4.5x per year while training data sets mushroom by 3x per year,2 etc.
Bigger, however, comes at a price. Data center power consumption threatens to nearly triple by 2028 primarily because of AI3. Water withdrawals, meanwhile, are escalating as well: by 2027, AI data centers could need up to 6.6 billion cubic meters, or about half of what the UK uses.4 The economic and environmental toll over the long run may not be sustainable.
Conceptually it is easier to understand how larger models translate into a "better and more capable" model. The more layers or parameters the models have, contribute to the quality and accuracy of the model. Yet, can we sustain that extracted value at the same cadence by continuing the size increase? Or will the curve start to plateau at some point?
-
November 05, 2023
Fibre Channel: The #1 Choice for Mission-Critical Shared-Storage Connectivity
By Todd Owens, Field Marketing Director, MarvellHere at Marvell, we talk frequently to our customers and end users about I/O technology and connectivity. This includes presentations on I/O connectivity at various industry events and delivering training to our OEMs and their channel partners. Often, when discussing the latest innovations in Fibre Channel, audience questions will center around how relevant Fibre Channel (FC) technology is in today’s enterprise data center. This is understandable as there are many in the industry who have been proclaiming the demise of Fibre Channel for several years. However, these claims are often very misguided due to a lack of understanding about the key attributes of FC technology that continue to make it the gold standard for use in mission-critical application environments.
From inception several decades ago, and still today, FC technology is designed to do one thing, and one thing only: provide secure, high-performance, and high-reliability server-to-storage connectivity. While the Fibre Channel industry is made up of a select few vendors, the industry has continued to invest and innovate around how FC products are designed and deployed. This isn’t just limited to doubling bandwidth every couple of years but also includes innovations that improve reliability, manageability, and security.
-
October 19, 2023
Shining a Light on Marvell Optical Technology and Innovation in the AI Era
By Kristin Hehir, Senior Manager, PR and Marketing, Marvell
The sheer volume of data traffic moving across networks daily is mind-boggling almost any way you look at it. During the past decade, global internet traffic grew by approximately 20x, according to the International Energy Agency. One contributing factor to this growth is the popularity of mobile devices and applications: Smartphone users spend an average of 5 hours a day, or nearly 1/3 of their time awake, on their devices, up from three hours just a few years ago. The result is incredible amounts of data in the cloud that need to be processed and moved. Around 70% of data traffic is east-west traffic, or the data traffic inside data centers. Generative AI, and the exponential growth in the size of data sets needed to feed AI, will invariably continue to push the curb upward.
Yet, for more than a decade, total power consumption has stayed relatively flat thanks to innovations in storage, processing, networking and optical technology for data infrastructure. The debut of PAM4 digital signal processors (DSPs) for accelerating traffic inside data centers and coherent DSPs for pluggable modules have played a large, but often quiet, role in paving the way for growth while reducing cost and power per bit.
Marvell at ECOC 2023
At Marvell, we’ve been gratified to see these technologies get more attention. At the recent European Conference on Optical Communication, Dr. Loi Nguyen, EVP and GM of Optical at Marvell, talked with Lightwave editor in chief, Sean Buckley, on how Marvell 800 Gbps and 1.6 Tbps technologies will enable AI to scale.
Recent Posts
- Auto-Load Balancing and Teralynx 10: Optimizing Cloud and AI Infrastructure
- Microsoft Azure Cloud Opens Services with FIPS-certified Marvell LiquidSecurity HSMs for Public Preview
- Advancing Optics with a Hybrid Route to TIAs
- Five Ways CXL Will Transform Computing
- In AI, The Voyage from Bigger to Better Is Underway
