AMD ROCm 7 Announced: MI350 Support, New Algorithms, Models & Advanced Features For A

[harlan4096]

AMD goes official with its next version of open software stack technologies in the form of ROCm 7, which further accelerates AI & developer productivity.

AMD Unveils ROCm 7: The Next-Generation of Open Stack Software Innovations With Focus on AI Inferencing

With the announcement of ROCm 7, AMD is finally moving forward from its ROCm 6 software stack, which itself has seen various updates over the last few years and since the advent of AI computing. The following are some of the main features that AMD is focusing on with ROCm 7:

• Latest Algorithms & Models
  
• Advanced Features for Scaling AI
  
• MI350 series support
  
• Cluster Management
  
• Enterprise Capabilities
  

 

With ROCm, AMD says that it is focusing more on the growing inference capabilities within its software stack. The ROCm 7 stack will include enhanced frameworks such as vLLM v1, llm-d, SGLang, and also focuses on serving various optimizations such as Distributed Inference, Prefill, and Disaggregation. New Kernels and Algorithms coming to ROCm 7 include GEMM Autotuning, MoE, Attention, and Python-Based Kernel Authoring.



AMD has already announced FP6 and FP4 support for its MI350 series, and ROCm 7 also includes full support for these advanced datatypes such as FP8, FP6, FP4, and Mixed precision.

In terms of performance, AMD says that inference has been the largest area of focus with ROCm 7, adding up to 3.5x performance uplifts in AI workloads. Breaking down the performance uplifts, we can see up to a 3.2x increase in Llama 3.1 70B, a 3.4x increase in Qwen2-72B, and up to 3.8x in Deep Seek R1, versus ROCm 6.

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[harlan4096]

AMD introduces ROCm 7, with higher performance and support for new hardware