Microsoft and AMD Extend AI Collaboration at Build
I sat in on Andrew Dieckmann and Nidhi Chappell’s session at MS Build today to learn more about how Microsoft is delivering new AI capability leveraging the MI300X accelerator. Andrew leads Instinct accelerator development at AMD, and Nidhi oversees Azure AI and HPC infrastructure at Microsoft. While today’s MI300X instance delivery is a tremendous milestone for the companies, this has been a multi-year journey in the making starting in 2020 with the MI50 accelerator instance which was focused on a small scale cluster implementation.
Andrew called out that generative AI is the most demanding data center workload requiring incredible performance and capability from infrastructure and specifically silicon. The MI300X has been designed to integrate AMD technologies and manufacturing prowess to deliver a compelling choice of solutions to the marketplace. Nidhi furthered this concept, stating that until today’s launch, Microsoft did not have a choice of solutions to offer customers being limited to NVIDIA instances. For those customers who are seeking higher memory capacity and better price performance, the AMD based instances provide notable value.
She extended this thought by stating that this is not just about a silicon optimization but a holistic view across data center, AI accelerator, CPU, IO and network optimization, delivering the infrastructure environment that allows Microsoft to keep pace with broader corporate objectives on scaling both performance capability and energy efficiency within the Azure environment. Nidhi’s team is leveraging MI300X for Microsoft’s own Azure AI, a stunning group of workloads that collectively delivers 7.5 trillion characters translated per month, 54 million meeting hours transcribed in Teams per month, and 100 million monthly active users of AI text predictions per month. While she didn’t go into detail on how much of this work is delivered using MI300X today, we recommend watching this space for growth of platform usage given the value the platform represents to generative AI.
One notable observation from the discussion was the centrality of low-latency access to data for generative AI. Nidhi and Andrew both discussed the capabilities offered with the MI300X platform in HBM memory support as well as platform memory capacity scale. Another attribute of note was the central focus on Hugging Face and their use of MI300X services giving callouts to the software optimizations as well as core platform capability as differentiating factors for their use.
Congrats to Microsoft and AMD for this great milestone. We at the TechArena can’t wait to see more collaborative innovation.
I sat in on Andrew Dieckmann and Nidhi Chappell’s session at MS Build today to learn more about how Microsoft is delivering new AI capability leveraging the MI300X accelerator. Andrew leads Instinct accelerator development at AMD, and Nidhi oversees Azure AI and HPC infrastructure at Microsoft. While today’s MI300X instance delivery is a tremendous milestone for the companies, this has been a multi-year journey in the making starting in 2020 with the MI50 accelerator instance which was focused on a small scale cluster implementation.
Andrew called out that generative AI is the most demanding data center workload requiring incredible performance and capability from infrastructure and specifically silicon. The MI300X has been designed to integrate AMD technologies and manufacturing prowess to deliver a compelling choice of solutions to the marketplace. Nidhi furthered this concept, stating that until today’s launch, Microsoft did not have a choice of solutions to offer customers being limited to NVIDIA instances. For those customers who are seeking higher memory capacity and better price performance, the AMD based instances provide notable value.
She extended this thought by stating that this is not just about a silicon optimization but a holistic view across data center, AI accelerator, CPU, IO and network optimization, delivering the infrastructure environment that allows Microsoft to keep pace with broader corporate objectives on scaling both performance capability and energy efficiency within the Azure environment. Nidhi’s team is leveraging MI300X for Microsoft’s own Azure AI, a stunning group of workloads that collectively delivers 7.5 trillion characters translated per month, 54 million meeting hours transcribed in Teams per month, and 100 million monthly active users of AI text predictions per month. While she didn’t go into detail on how much of this work is delivered using MI300X today, we recommend watching this space for growth of platform usage given the value the platform represents to generative AI.
One notable observation from the discussion was the centrality of low-latency access to data for generative AI. Nidhi and Andrew both discussed the capabilities offered with the MI300X platform in HBM memory support as well as platform memory capacity scale. Another attribute of note was the central focus on Hugging Face and their use of MI300X services giving callouts to the software optimizations as well as core platform capability as differentiating factors for their use.
Congrats to Microsoft and AMD for this great milestone. We at the TechArena can’t wait to see more collaborative innovation.
