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llama.cpp removes key performance flag, developers find new ways to boost speed

By PulseAugur Editorial · [1 sources] ·

A developer details the loss and eventual replacement of a crucial performance flag, `-sm row`, in the llama.cpp project. Initially, this flag significantly boosted throughput for multi-GPU setups by splitting tensors across devices. However, issues arose with newer architectures like Gemma, which caused crashes with the row split, forcing a switch to a slower layer split. Ultimately, the `-sm row` flag was entirely removed from llama.cpp, but performance was recovered and even surpassed through orthogonal features like parallel processing and speculative decoding. AI

IMPACT Illustrates how software updates and architectural changes in foundational tools can impact performance and require adaptation.

RANK_REASON Developer's personal account of a software change and its impact on their workflow.

Read on dev.to — LLM tag →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

llama.cpp removes key performance flag, developers find new ways to boost speed

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Developer's personal account of a software change and its impact on their workflow.
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COVERAGE [1]

  1. dev.to — LLM tag TIER_1 English(EN) · dev-brewery ·

    The Flag We Tuned Around Got Deleted

    <p>The single most important llama.cpp flag for my dual Tesla P40 setup was <code>-sm row</code>. It split every layer's tensors across both GPUs and it was worth nearly double the throughput of the alternative: 12-14 tokens/sec against about 7 for layer split. Every stack I buil…

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