GPGPU Compute Cluster Preemption via Thread Context Extraction
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Solution Overview
Problem
Current graphics processing systems face inefficiencies in parallel data processing due to limitations in preemption mechanisms, leading to stalled compute clusters and reduced utilization, especially in GPGPU environments where deep pipeline stages and large pipeline state require high latency for preemption.
Innovation Solution
Implementing a preemptable GPGPU compute system with a hardware mechanism for tracking blocking events, enabling workload rebalancing and fine-grained thread saving and switching, as well as low latency preemption techniques that reduce the amount of pipeline state required to be saved, allowing for efficient migration and restoration of compute tasks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If traditional preemption mechanisms are used in GPGPU systems, then pipeline state can be saved, but preemption latency becomes high due to deep pipeline stages and large pipeline state
Solution Approach 1:
The patent segments the pipeline state into critical and non-critical components, saving only the essential register state and control information rather than the entire pipeline state. This selective saving approach reduces the amount of data that needs to be preserved during preemption, thereby reducing preemption latency while maintaining the ability to restore compute cluster functionality.
Solution Approach 2:
The invention extracts and saves only the necessary thread context information (register state, program counter, etc.) during preemption, separating this critical data from the larger pipeline state. By taking out only the essential elements for thread restoration, the system achieves fast preemption without requiring preservation of the complete pipeline state.
2Productivity
If compute clusters are preempted to improve resource utilization, then workload can be rebalanced, but context switching time increases
Solution Approach 1:
The patent implements preliminary actions by continuously monitoring compute cluster status and preparing thread context for potential preemption. The system maintains ready queues and pre-allocates resources, so when preemption is needed, threads can be quickly switched without requiring extensive context restoration, thereby reducing context switching time while enabling frequent workload rebalancing.
Solution Approach 2:
The invention changes the preemption granularity parameter from cluster-level to thread-level preemption. By enabling individual thread preemption within a compute cluster rather than preempting the entire cluster, the system can perform frequent context switches with minimal overhead, improving both productivity and reducing time loss.
3Productivity
If fine-grained thread saving and switching is implemented, then preemption efficiency improves, but hardware complexity increases
Solution Approach 1:
The patent makes the thread context saving mechanism universal by implementing a unified hardware structure that handles both thread context saving and compute cluster scheduling functions. The same hardware components used for thread state management also support fine-grained preemption operations, eliminating the need for separate dedicated hardware and reducing overall system complexity while maintaining high preemption efficiency.
Data Source
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AI summary
One embodiment provides for a general-purpose graphics processing unit comprising a compute cluster including multiple compute units, a stall notification module to detect that one or more compute units in the compute cluster are stalled and send stall notification, and a rebalance module to receive the stall notification, the rebalance module to migrate a first workload from one or more stalled compute units in response to the stall notification.