name: kernel_writer
version: 1.0.0
description: |
  Real world CUDA kernel engineering environment for iterative optimization, code review checks and performance driven reward shaping.

environment:
  type: code_optimization
  runtime: python3.12.3
  containerized: true

metadata:
  tags:
    - openenv
    - CUDA
    - kernel_optimization
    - reinforcement_learning
  author: aaloksan

tasks:
  - id: vector_add_easy
    name: "Vector Addition Kernel Optimization"
    difficulty: easy
    objective: "Improve memory throughput while preserving correctness."
    grader: deterministic_rule_based

  - id: matmul_medium
    name: "Matrix Multiplication Kernel Optimization"
    difficulty: medium
    objective: "Apply shared-memory tiling and synchronization safely."
    grader: deterministic_rule_based

  - id: reduction_hard
    name: "Reduction Kernel Optimization"
    difficulty: hard
    objective: "Use warp-level optimization and reduce memory conflicts."
    grader: deterministic_rule_based

interfaces:
  reset:
    method: POST
    path: /reset
    returns: initial observation, metadata info
  step:
    method: POST
    path: /step
    returns: observation, reward, done, info
  state:
    method: GET
    path: /state
    returns: current environment state

baseline:
  script: inference.py
  model_env_var: MODEL_NAME
  api_key_env_var: OPENAI_API_KEY