─ Newest accelerators provide market main HBM3E reminiscence capability and are supported by companions and prospects together with Dell Applied sciences, HPE, Lenovo, Supermicro and others ─
─ AMD Pensando Salina DPU gives 2X generational efficiency and AMD Pensando Pollara 400 is {industry}’s first UEC prepared NIC─
AMD introduced the most recent accelerator and networking options that can energy the following era of AI infrastructure at scale: AMD Intuition MI325X accelerators, the AMD Pensando Pollara 400 NIC and the AMD Pensando Salina DPU. AMD Intuition MI325X accelerators set a brand new commonplace in efficiency for Gen AI fashions and knowledge facilities.
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Constructed on the AMD CDNA 3 structure, AMD Intuition MI325X accelerators are designed for distinctive efficiency and effectivity for demanding AI duties spanning basis mannequin coaching, fine-tuning and inferencing. Collectively, these merchandise allow AMD prospects and companions to create extremely performant and optimized AI options on the system, rack and knowledge middle stage.
“AMD continues to ship on our roadmap, providing prospects the efficiency they want and the selection they need, to convey AI infrastructure, at scale, to market sooner,” mentioned Forrest Norrod, govt vp and normal supervisor, Knowledge Middle Options Enterprise Group, AMD. “With the brand new AMD Intuition accelerators, EPYC processors and AMD Pensando networking engines, the continued development of our open software program ecosystem, and the power to tie this all collectively into optimized AI infrastructure, AMD underscores the essential experience to construct and deploy world class AI options.”
AMD Intuition MI325X Extends Main AI Efficiency
AMD Intuition MI325X accelerators ship industry-leading reminiscence capability and bandwidth, with 256GB of HBM3E supporting 6.0TB/s providing 1.8X extra capability and 1.3x extra bandwidth than the H200. The AMD Intuition MI325X additionally gives 1.3X better peak theoretical FP16 and FP8 compute efficiency in comparison with H200.
This management reminiscence and compute can present as much as 1.3X the inference efficiency on Mistral 7B at FP16, 1.2X the inference efficiency on Llama 3.1 70B at FP8 and 1.4X the inference efficiency on Mixtral 8x7B at FP16 of the H200.
AMD Intuition MI325X accelerators are presently on observe for manufacturing shipments in This autumn 2024 and are anticipated to have widespread system availability from a broad set of platform suppliers, together with Dell Applied sciences, Eviden, Gigabyte, Hewlett Packard Enterprise, Lenovo, Supermicro and others beginning in Q1 2025.
Persevering with its dedication to an annual roadmap cadence, AMD previewed the next-generation AMD Intuition MI350 collection accelerators. Based mostly on AMD CDNA 4 structure, AMD Intuition MI350 collection accelerators are designed to ship a 35x enchancment in inference efficiency in comparison with AMD CDNA 3-based accelerators.
The AMD Intuition MI350 collection will proceed to drive reminiscence capability management with as much as 288GB of HBM3E reminiscence per accelerator. The AMD Intuition MI350 collection accelerators are on observe to be out there through the second half of 2025.
AMD Subsequent-Gen AI Networking
AMD is leveraging essentially the most broadly deployed programmable DPU for hyperscalers to energy next-gen AI networking. Cut up into two components: the front-end, which delivers knowledge and data to an AI cluster, and the backend, which manages knowledge switch between accelerators and clusters, AI networking is essential to making sure CPUs and accelerators are utilized effectively in AI infrastructure.
To successfully handle these two networks and drive excessive efficiency, scalability and effectivity throughout all the system, AMD launched the AMD Pensando Salina DPU for the front-end and the AMD Pensando™ Pollara 400, the {industry}’s first Extremely Ethernet Consortium (UEC) prepared AI NIC, for the back-end.
The AMD Pensando Salina DPU is the third era of the world’s most performant and programmable DPU, bringing as much as 2X the efficiency, bandwidth and scale in comparison with the earlier era. Supporting 400G throughput for quick knowledge switch charges, the AMD Pensando Salina DPU is a essential part in AI front-end community clusters, optimizing efficiency, effectivity, safety and scalability for data-driven AI purposes.
The UEC-ready AMD Pensando Pollara 400, powered by the AMD P4 Programmable engine, is the {industry}’s first UEC-ready AI NIC. It helps the next-gen RDMA software program and is backed by an open ecosystem of networking. The AMD Pensando Pollara 400 is essential for offering management efficiency, scalability and effectivity of accelerator-to-accelerator communication in back-end networks.
Each the AMD Pensando Salina DPU and AMD Pensando Pollara 400 are sampling with prospects in This autumn’24 and are on observe for availability within the first half of 2025.
AMD AI Software program Delivering New Capabilities for Generative AI
AMD continues its funding in driving software program capabilities and the open ecosystem to ship highly effective new options and capabilities within the AMD ROCm open software program stack.
Throughout the open software program group, AMD is driving assist for AMD compute engines in essentially the most broadly used AI frameworks, libraries and fashions together with PyTorch, Triton, Hugging Face and lots of others. This work interprets to out-of-the-box efficiency and assist with AMD Intuition accelerators on common generative AI fashions like Secure Diffusion 3, Meta Llama 3, 3.1 and three.2 and multiple million fashions at Hugging Face.
Past the group, AMD continues to advance its ROCm open software program stack, bringing the most recent options to assist main coaching and inference on Generative AI workloads. ROCm 6.2 now consists of assist for essential AI options like FP8 datatype, Flash Consideration 3, Kernel Fusion and extra. With these new additions, ROCm 6.2, in comparison with ROCm 6.0, offers as much as a 2.4X efficiency enchancment on inference and 1.8X on coaching for a wide range of LLMs.
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