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Abstract:

This video documents a lengthy live-streamed session where developer René Rebe attempts to compile AMD's ROCm (Radeon Open Compute platform) GPU compute stack for AI workloads (specifically targeting Llama.cpp) on a high-core-count RISC-V system (Sophgo Milk-V Pioneer "Ripper" with 64 cores/128GB RAM) using the T2 SDE Linux distribution. The stream highlights the significant challenges involved in porting such a complex software suite to a non-mainstream architecture. Key difficulties include navigating extremely inconsistent and often broken CMake build configurations across different ROCm components (using varying variable names like hip_ARCHITECTURES, GPU_TARGETS, AMD_GPU_TARGETS), resolving numerous dependency issues related to hardcoded paths and library linking errors, and battling exceptionally long build and link times (often exceeding 40 minutes for linking single components on RISC-V) exacerbated by single-threaded bottlenecks and software bloat. Despite applying numerous patches and workarounds, and successfully building some components and even Llama.cpp with ROCm support on an x86_64 system, the effort is ultimately halted by a critical segmentation fault within the clang compiler while building the rocksolver library on the RISC-V hardware, demonstrating the arduous nature of this porting task.

Building ROCm and AI on RISC-V: A Debugging Journey

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