Processor Thread Allocation via Delay-Cost Scheduling
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Solution Overview
Problem
Conventional schedulers for multi-threaded processors in modern computer systems fail to efficiently schedule multiple simultaneously executing threads and do not explicitly address tradeoffs associated with core or hardware thread assignments, nor do they consider energy usage in hypervisor contexts.
Innovation Solution
A scheduler that allocates hardware threads based on priorities and delay-costs, optimizing the sum of priorities or generalized delay-costs, while considering energy consumption and fairness criteria, to balance the system load by distributing guest operating systems across processor pools.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional schedulers assign fair share time slices to each guest operating system, then fairness is improved, but the ability to handle multiple simultaneously executing threads and optimize for energy usage deteriorates
Solution Approach 1:
The scheduler dynamically adjusts time slice allocations based on real-time conditions including thread priorities, delay costs, and energy consumption metrics. The fair share concept is made dynamic by allowing guests to receive different time slice lengths based on their current state, requested threads, and energy efficiency considerations, rather than fixed equal portions.
Solution Approach 2:
The system changes multiple scheduling parameters simultaneously including time slice duration, priority levels, and allocation decisions based on a comprehensive evaluation of delay costs and energy consumption. This multi-parameter optimization allows the scheduler to balance fairness with performance and energy efficiency.
2Productivity
If the scheduler allocates more hardware threads to guest operating systems, then processing capability is improved, but energy consumption increases
Solution Approach 1:
The scheduler optimizes the number of hardware threads allocated to each guest by evaluating delay costs and energy consumption together. It dynamically adjusts thread allocation parameters to achieve the optimal balance where additional threads provide sufficient performance improvement while keeping energy consumption within acceptable limits.
Solution Approach 2:
The system incorporates feedback mechanisms that monitor energy consumption and adjust thread allocations accordingly. The scheduler uses delay cost calculations that factor in energy usage, allowing it to reduce thread allocation when performance needs are low and increase allocation when critical performance requirements exist.
3Productivity
If the scheduler optimizes the sum of generalized delay-costs, then scheduling efficiency is improved, but system complexity increases
Solution Approach 1:
The scheduling problem is segmented into manageable components: calculating individual delay costs for each guest, determining generalized delay costs that incorporate energy factors, and then optimizing the overall allocation. This breakdown of the complex optimization problem into discrete steps makes the algorithm more implementable and maintainable.
Data Source
AI summary
A computer system includes a plurality of multi-threaded processors, and a scheduler. The multi-threaded processors each have a set of hardware threads forming a pool of hardware threads. The scheduler allocates hardware threads of the pool of hardware threads to one or more guest operating systems based on priorities of the guest operating systems. The priorities of the guest operating systems are based on logical processors requested by the guest operating systems.