Going forward, we see this trend only accelerating. And it is important to note that these DSPs are compatible with a variety of network protocols such as Ethernet, InfiniBand and other proprietary solutions for maximum breadth and flexibility. This way AI is a strong growth driver for our PAM4 optical DSP platform. utilizing digital signal processing and the latency high-capacity fabric switches. This connectivity is best provided by wholly optically connected infrastructure. These clusters require a staggering amount of high-bandwidth connectivity, all of which needs to be provided at ultra-low latency and high reliability and within a reasonable power outlook. Keep in mind, these cloud data centers connect thousands of these systems in a single cluster to provide maximum scalability for their customers with each of these systems capable of driving tens of terabits of network traffic.Īnd in order to create the largest possible cluster sizes at data center scale, these connections need to be able to operate over increasingly long distances. That's hundreds of times more bandwidth required to connect these systems together. In contrast, an example of an advanced AI system containing 8 accelerators can drive close to 30 terabits of full duplex bandwidth. To give you an idea, the latest dual CPU server in a cloud data center today can drive up to 200 gigabits per second of IO and contains the network interfaces to support that bandwidth. Bandwidth required to interconnect these systems is orders of magnitude higher than in standard cloud infrastructure. In large deployments, thousands of these systems are interconnected to form a data center-sized AI cluster. Rather than dual-socket servers as the core element in, the primary building block in AI is a system containing multiple accelerators such as GPUs. To efficiently process this data, the architecture for AI data centers is significantly different than standard cloud infrastructure. Today's AI workloads require a truly massive data sets. Generative AI is rapidly driving new applications and changing the investment priorities for our cloud customers. In the past, we considered AI to be one of many applications within cloud, but its importance and therefore, the opportunity has increased dramatically. My questions regarding the below if anyone bothers to read, does this require bandwidth outside the data center or is this all internal? I have always thought data centers and the cloud are responsible for much of Lumens diminished returns, curious if this is more of that or something else?īefore we get to our results for each end market, let me start by discussing the tremendous opportunity that AI represents for Marvell. I believe it is from the Marvel conference call. Interesting AI commentary from an IV poster that comes around here every once in a while.
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