Data Parallel Runtime Transparent Device Transfer
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Solution Overview
Problem
Conventional data parallel programming models face challenges in handling device removal or de-provisioning, leading to abnormal program termination and increased error handling costs, which degrades their effectiveness in diverse workload processing across heterogeneous devices.
Innovation Solution
Implementing a data parallel programming runtime that can transparently switch to a compatible device when a notification of de-provisioning occurs, allowing workloads to continue executing without user intervention, and enabling automatic migration to more efficient devices when available.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional data parallel programming models are used, then workloads can be processed on hardware accelerators, but the system terminates abnormally when a device is removed or de-provisioned
Solution Approach 1:
The system dynamically adapts to device status changes by implementing a runtime mechanism that detects device removal and automatically transfers execution to alternative devices. This dynamic behavior allows the programming model to maintain reliability while adapting to heterogeneous device environments, resolving the contradiction between execution reliability and adaptability to device changes.
Solution Approach 2:
An intermediary runtime layer is introduced between the application and hardware accelerators to manage device lifecycle events. This intermediary detects device de-provisioning notifications and orchestrates the transfer of workload execution to alternative devices, preventing abnormal termination while maintaining system adaptability to device changes.
2Reliability
If device transfer is implemented, then workload continuity is maintained, but system complexity increases
Solution Approach 1:
The runtime system implements self-service mechanisms by automatically detecting device status changes and performing transfer operations without requiring explicit user intervention. The system monitors device de-provisioning events and autonomously executes transfer logic, maintaining workload continuity while managing complexity through automated self-management rather than manual control.
Solution Approach 2:
The system employs feedback mechanisms by monitoring device status notifications and using this information to trigger transfer operations. The runtime receives feedback about device de-provisioning events and automatically responds by transferring execution to alternative devices, ensuring workload continuity while managing system complexity through event-driven feedback loops.
3Reliability
If automatic device switching is enabled, then error handling costs are reduced, but transparency and ease of operation may be compromised
Solution Approach 1:
The runtime system performs automatic device transfer operations without requiring user intervention, making the error handling transparent to users. The system autonomously detects device removal events and executes transfer logic, reducing error handling costs while maintaining ease of operation through fully automated self-service behavior that users do not need to manage manually.
Data Source
AI summary
An apparatus to facilitate data parallel programming-based transparent transfer across heterogeneous devices is disclosed. The apparatus includes a processor to: identify a change in device status that triggers a device transfer process from an original device, wherein the original device is associated with a queue of an application program of a data parallel programming runtime; identify a new device that is compatible with the original device; migrate at least one of a state or data of the original device to the new device; logically map, without user intervention, the queue to the new device in the data parallel programming runtime; and initiate execution of the application program on the new device using the queue.