Client scheduling policies

The client embodies two related scheduling policies:

Task scheduling policy

Of the tasks that are runnable, which ones to execute?

Work-fetch policy

When to ask a project for more work, which project to ask, and how much work of each processor type to ask for?

Note: a processor type is either CPU or a GPU vendor. There may be multiple instances of each processor type.

The goals of these policies are (in descending priority):

1. Tasks should be completed and reported by their deadline (results reported after their deadline may not have any value to the project and may not be granted credit).
2. All processors should be kept busy.
3. At any given point, the computer should have enough work so that its processors will be busy for at least min_buf days and not much more than max_buf days.
4. Project resource shares should be honored over the long term.
5. If a computer is attached to multiple projects, execution should rotate among projects on a frequent basis to improve the volunteer experience.

Task scheduling simulation

The baseline task scheduling policy is weighted round-robin (WRR): one-hour time slices are given to projects in turn, with the number of time slices in proportion to the project's resource share.

Both task scheduling and work-fetch policies involve first simulating the execution of existing tasks in FIFO order under the WRR policy. This simulation produces several outputs:

• For each processor type, the shortfall: that is, the number additional instance-seconds needed to keep all instances busy until max_buffer. In the example below, the shortfall (the gray areas) is 13.

• For each processor type, the number of currently idle instances.

• For each processor type, the saturated: the amount of time that all instances are busy.

• For each task T, a flag T.deadline_miss indicating whether the task missed its deadline in the simulation.

After doing the WRR simulation, a second simulation is done in which tasks that missed their deadline are executed in EDF order. For each resource type, this yields a busy time, which is the period during which all instances are busy in this simulation. This is passed to the scheduler; its significance is that no new jobs can possibly be started before this time.

Project scheduling priority

Both scheduling policies involve a notion of project scheduling priority, a dynamic quantity that reflects how much processing has been done recently by the project's tasks relative to its resource share.

The scheduling priority of a project P is computed as

SP(P) = - REC(P)/resource_share(P)

where REC(P) is the amount of processing done recently by P. REC and resource_share are normalized to sum to 1 over all projects.

Job scheduling

The job scheduling policy is roughly as follows:

• For each GPU type, schedule deadline-miss tasks in order of increasing deadline, until all instances are used.
• Same for CPU.
• For each GPU type, while there are still available instances, schedule non-deadline-miss tasks in order of project scheduling priority.
• Same for CPU.

As each job is scheduled, we increment a copy of REC(P) as if the job had run for one scheduling period. This encourages the scheduler to pick jobs from the same project.

Work fetch

The work fetch policy:

• Work fetch for a given processor type is initiated whenever the saturated period is less than min_buffer.
• Adjust SP(P) based on the amount of work currently queued
• Ask the fetchable project with greatest SP(P) for "shortfall" seconds of work.
• Whenever a scheduler RPC to project P is done (e.g. to report results) and SP(P) is greatest among fetchable projects for a given processor type, request "shortfall" seconds of that type.