Real-Time Multi-Thread Performance | Dataford Interview Questions

How do you ensure real-time performance in a multi-threaded application?

Implement a deterministic worker scheduler that assigns tasks to the earliest available worker. Process tasks by release time, preserve input order for equal release times, and break worker ties by worker ID.

The function receives tasks, a list of [release_time, duration] pairs, and worker_count. Return completion times in the original task order, where each task starts at max(release_time, worker_available_time).

Constraints

1 <= len(tasks) <= 1000
1 <= worker_count <= 100
0 <= release_time <= 10^9
0 <= duration <= 10^9
Each task is represented as [release_time, duration]

Function Signature

def schedule_tasks(tasks, worker_count):

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Problem

How do you ensure real-time performance in a multi-threaded application?

Constraints

1 <= len(tasks) <= 1000
1 <= worker_count <= 100
0 <= release_time <= 10^9
0 <= duration <= 10^9
Each task is represented as [release_time, duration]

Function Signature

def schedule_tasks(tasks, worker_count):

Your question is Real-Time Multi-Thread Performance. Start with the requirements in the Question tab.

Run and submit as often as you like. When you're ready, talk me through your approach or go straight to the code.