project_6

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Author	SHA1	Message	Date
EngineX CI	e7fdf5777a	[DOC] Add MUH project checkpoint — single source of truth for context continuity This document allows any new Claude session to pick up exactly where the current session left off. Contains: - Competition rules and scoring formula - Testing pipeline (how the platform evaluates submissions) - muh language architecture (3-layer: schema → config → codegen) - All completed work (issues #1-#25) - What's next - Key file paths and parameters	2026-07-30 09:59:15 +00:00
EngineX CI	56fd68e7dd	[INFRA] Import NVIDIA/CCCL upstream as optimization reference library CCCL (CUDA C++ Core Libraries) provides: - CUB: device/block/warp-level GPU primitives (reduce, scan, sort, topk) - Thrust: high-level parallel algorithms (transform_reduce, sort, scan) - libcudacxx: CUDA C++ standard library (atomics, barriers, memory) - cudax: experimental features (memory resources, allocators) - Tuning policies: per-SM hardware-specific algorithm parameters Competition optimization vectors mapped to CCCL: - Output TPS (83% weight): warp_reduce, block_reduce, device_topk - Input TPS (14% weight): device_scan, block_load, prefetch - Cache TPS (3% weight): prefix caching strategy patterns - Memory (0.9 util): pooled/cached/buddy allocators Source: https://github.com/NVIDIA/cccl (shallow clone, HEAD only) License: Apache-2.0	2026-07-30 09:35:51 +00:00
dylanyunlon	b4d01f481e	Initial commit	2026-07-30 17:03:23 +08:00

Author

SHA1

Message

Date

EngineX CI

e7fdf5777a

[DOC] Add MUH project checkpoint — single source of truth for context continuity

This document allows any new Claude session to pick up exactly where
the current session left off. Contains:
- Competition rules and scoring formula
- Testing pipeline (how the platform evaluates submissions)
- muh language architecture (3-layer: schema → config → codegen)
- All completed work (issues #1-#25)
- What's next
- Key file paths and parameters

2026-07-30 09:59:15 +00:00

EngineX CI

56fd68e7dd

[INFRA] Import NVIDIA/CCCL upstream as optimization reference library

CCCL (CUDA C++ Core Libraries) provides:
- CUB: device/block/warp-level GPU primitives (reduce, scan, sort, topk)
- Thrust: high-level parallel algorithms (transform_reduce, sort, scan)
- libcudacxx: CUDA C++ standard library (atomics, barriers, memory)
- cudax: experimental features (memory resources, allocators)
- Tuning policies: per-SM hardware-specific algorithm parameters

Competition optimization vectors mapped to CCCL:
- Output TPS (83% weight): warp_reduce, block_reduce, device_topk
- Input TPS (14% weight): device_scan, block_load, prefetch
- Cache TPS (3% weight): prefix caching strategy patterns
- Memory (0.9 util): pooled/cached/buddy allocators

Source: https://github.com/NVIDIA/cccl (shallow clone, HEAD only)
License: Apache-2.0

2026-07-30 09:35:51 +00:00

dylanyunlon

b4d01f481e

Initial commit

2026-07-30 17:03:23 +08:00