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AMEVA-Runtime (Python)

PyPI Python License

모바일 및 엣지 환경을 위한 차세대 통합 온디바이스 하드웨어 오케스트레이션 및 멀티모달 가속 런타임
Next-Gen Unified On-Device Hardware Orchestration & Multi-Modal Acceleration Runtime for Mobile & Edge

Installation

pip install ameva-runtime

Quickstart

import ameva_runtime as ameva

# 1. Execute LLM inference directly with optimal on-device hardware dispatch
result = ameva.run(
    model="qwen2.5-0.5b",
    prompt="Space in Korean is:",
    max_tokens=32
)

print(f"Generated text: {result.text}")
print(f"Hardware backend: {result.backend_used} ({result.tokens_per_second:.2f} t/s)")

# 2. Preview hardware execution plan
plan = ameva.plan(model="qwen2.5-0.5b")
print(f"Route: {plan.backend} | NGL: {plan.ngl} | Threads: {plan.threads}")

Description

AMEVA Runtime provides a unified, zero-silent-fallback hardware orchestration engine for generative AI on mobile and edge devices. It automatically resolves vendor divergence, dispatching to native Vulkan hardware offload on Qualcomm Adreno while isolating driver deadlocks on ARM Mali through deterministic Cortex-A78 CPU-NEON multi-threading.

Empirical Hardware Benchmarks (Qwen2.5-0.5B-Instruct)

Device & SoC GPU & Driver Architecture Backend Route Layer Offload Generation Speed Prompt Eval Speed UI Freeze Speedup
Galaxy S25 (Snapdragon 8 Elite) Qualcomm Adreno 830 (Vulkan 1.3) VULKAN 25/25 (100% VRAM) 35.80 t/s (27.93 ms/t) 4.53 t/s 0% 35.8x
Galaxy A35 (Exynos 1380) ARM Mali-G68 MP5 (Vulkan 1.3) CPU-NEON 0/25 (Safe Guard) 3.55 t/s (295 ms/t) 8.05 t/s 0% Baseline
Galaxy A35 (Forced Vulkan Test) ARM Mali-G68 MP5 (vulkan.mali.so) VULKAN 25/25 0.00 t/s (Deadlock) - 100% (Hung) Failed

Technical Rationale for ARM Mali CPU-NEON Fallback

The proprietary ARM Mali Vulkan driver (/vendor/lib64/hw/vulkan.mali.so via /dev/mali0) enforces aggressive kernel-level dynamic power management (DVFS) tied to SurfaceFlinger display composition. During headless compute dispatches in terminal or CLI environments (lacking an active window swapchain), the Mali driver interprets the absence of display flips as an idle state, downclocking GPU compute cores and failing to signal in-flight completion fences. This causes host threads waiting on vkWaitForFences or vkQueueWaitIdle to deadlock indefinitely.

To guarantee rock-solid system stability and eliminate device lockups, the AMEVA SmartRouter automatically identifies ARM Mali GPUs, bypasses the unstable headless Vulkan path, and dispatches inference to the high-performance ARM Cortex-A78 CPU-NEON cluster.

CLI Quickstart

# 1. Automatic hardware diagnosis and profile inspection
ameva-run doctor
ameva-run profile

# 2. Dry-run execution plan
ameva-run plan -m qwen2.5-0.5b

# 3. Direct model execution with automatic hardware acceleration
ameva-run exec -m qwen2.5-0.5b -p "Space in Korean is:" -n 32

Documentation

License

Apache-2.0 License. Copyright (c) 2026 Eunho Kim (@uno-km).

Release files for ameva-runtime 1.0.0

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