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Feature/e2k support#26107

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png-tech:feature/e2k_support
Open

Feature/e2k support#26107
png-tech wants to merge 2 commits into
ggml-org:masterfrom
png-tech:feature/e2k_support

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@png-tech

@png-tech png-tech commented Jul 25, 2026

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Overview

Add native e2k (Elbrus 2000) support to llama.cpp for CPU-based inference.

Motivation:

Enable efficient local inference on Elbrus-based systems (e.g., Elbrus‑8SV) using ggml-cpu backends, with attention to instruction compatibility, floating-point semantics, and memory access patterns specific to the e2k architecture.

Changes:

  • Add e2k-specific detection and backend selection logic.
  • Disable or replace x86-specific intrinsics (e.g., F16C, AVX, etc.) with portable or e2k-appropriate implementations.
  • Adjust math and quantization paths to avoid relying on unsupported instructions.
  • Verify correctness and performance with common quantized formats (Q4_K_M, Q5_K_M, Q8_0).

Benefits:

  • Allows running llama.cpp natively on e2k without illegal instruction faults.
  • Maintains acceptable inference speed on CPU-only Elbrus setups.
  • Improves portability for users targeting domestic/specialized hardware.

Requirements

@png-tech
png-tech requested a review from ggerganov as a code owner July 25, 2026 04:25
@github-actions github-actions Bot added the ggml changes relating to the ggml tensor library for machine learning label Jul 25, 2026
@ggml-gh-bot

ggml-gh-bot Bot commented Jul 25, 2026

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Hi @png-tech, thanks for your contribution!

Per our contribution guidelines, the automated PR checker found the following issue(s) that need your attention:

  • PR Template not respected: Please respect the template when creating a new pull request. Make sure to fill out all required sections.

Please note that maintainers reserve the right to make final decisions on PRs. If you believe there is a mistake, please comment below.

@png-tech png-tech closed this Jul 25, 2026
@png-tech png-tech reopened this Jul 25, 2026
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