{
  "context": "This criteria evaluates how well the engineer uses PyOpenCL's event profiling features to measure kernel and operation execution times with nanosecond precision. The focus is on proper use of profiling-enabled command queues, event objects, and timing property access.",
  "type": "weighted_checklist",
  "checklist": [
    {
      "name": "Profiling-enabled queue",
      "description": "Creates a CommandQueue with the PROFILING_ENABLE property to enable event timing measurements.",
      "max_score": 20
    },
    {
      "name": "Event capture",
      "description": "Captures Event objects returned from enqueue operations (kernel execution, buffer transfers) to enable timing measurements.",
      "max_score": 15
    },
    {
      "name": "Event wait",
      "description": "Calls wait() on events or uses queue.finish() to ensure operations complete before reading timing information.",
      "max_score": 15
    },
    {
      "name": "Profile timing access",
      "description": "Accesses timing information using event.profile.start and event.profile.end (or equivalent profile attributes like event.profile.submit, event.profile.complete).",
      "max_score": 25
    },
    {
      "name": "Duration calculation",
      "description": "Correctly calculates execution duration by subtracting start time from end time to get nanosecond-precision timing.",
      "max_score": 15
    },
    {
      "name": "Multiple operation profiling",
      "description": "Demonstrates ability to profile multiple independent operations and track their timings separately as required by the spec.",
      "max_score": 10
    }
  ]
}