Adaptive All-Reduce Offloading for AI Straggler Mitigation
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Solution Overview
Problem
Large AI models with distributed multi-node and multi-rack deployments face delays due to straggler processes, leading to network congestion, increased completion times, and violations of service level agreements (SLAs) during training and inference operations.
Innovation Solution
A network interface device tracks process durations and identifies stragglers by analyzing floating point operations per second (FLOPS) and completion times, performing remedial actions such as resource adjustments or process migration to optimize straggler performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If distributed multi-node and multi-rack deployments are used for large AI models, then processing capacity and scalability are improved, but network congestion and completion time increase due to straggler processes
Solution Approach 1:
The system performs preliminary identification of straggler processes by tracking process durations and analyzing FLOPS metrics before they cause significant delays. By detecting stragglers early in the execution timeline, the system can proactively migrate these processes to different nodes before they bottleneck the entire distributed computation, thus preventing completion time increases while maintaining high processing capacity
Solution Approach 2:
The patent introduces a network interface device as an intermediary between the distributed AI model processes and the underlying network infrastructure. This intermediary monitors process performance metrics, identifies stragglers, and coordinates their migration to different nodes, thereby mediating the conflict between maintaining distributed processing capacity and avoiding completion time delays caused by network congestion
2Stability of the object's composition
If straggler processes are allowed to complete naturally, then system stability is maintained, but network congestion and service level agreement violations occur
Solution Approach 1:
The system implements continuous feedback loops by monitoring process duration metrics and FLOPS performance in real-time. When straggler processes are detected through this feedback mechanism, the system responds by migrating these processes to different nodes, thereby preventing network congestion and SLA violations while maintaining overall system stability through controlled rather than chaotic interventions
Solution Approach 2:
The patent applies dynamic process migration strategies where straggler processes are moved from static node assignments to dynamic reassignment based on real-time performance metrics. This dynamic approach allows the system to maintain stability by only moving necessary processes while improving reliability by preventing SLA violations that would occur if stragglers were allowed to complete naturally
3Loss of time
If process migration is performed to address stragglers, then completion time is reduced, but device complexity increases
Solution Approach 1:
The network interface device serves as a specialized intermediary that handles the complexity of straggler identification and process migration. By offloading these complex monitoring and coordination tasks to a dedicated intermediary component, the overall system achieves reduced completion times through effective straggler management while the complexity is localized to a specific device rather than distributed across all system components
Data Source
AI summary
Examples described herein relate to a network interface device that includes: a host interface; a direct memory access (DMA) circuitry; a network interface to receive, in at least one packet, time data associated with at least one of multiple layers, wherein the multiple layers provide inputs to a collective operation associated with a large language model (LLM); and circuitry. The circuitry is to based, at least in part, on the time data associated with the multiple layers, identify a first operation of a first layer of the multiple layers as a late completing process relative to times to completion of multiple first operations of other layers and based on the first operation being identified as a late completing process, perform a remedial action to adjust at least one configuration of a first device to execute a second operation of the first layer.