Latency-Hiding Context Management for Distributed Tasks
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Distributed data processing systems face performance bottlenecks due to communication latency, particularly in large-scale graph processing where numerous concurrent tasks require remote data access, leading to underutilization of computational resources.
Innovation Solution
Implementing a context management system with request and companion buffers that allow worker threads to suspend tasks during remote data access, enabling efficient processing by sending request messages and resuming tasks upon response, thereby hiding communication latency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If context switching with ready task queue and suspended task queue is implemented, then communication latency is hidden for small numbers of tasks, but the queues become a performance bottleneck when the number of remote data accesses and concurrent tasks is large
Solution Approach 1:
The patent segments the task management system into multiple worker threads, each independently managing its own ready task queue and suspended task queue. This segmentation allows parallel processing of tasks across multiple threads, preventing any single queue from becoming a system-wide bottleneck. Each worker thread can independently select and execute tasks from its own ready queue without contention from other threads, thereby maintaining high processing throughput even with large numbers of concurrent tasks.
Solution Approach 2:
The patent implements preliminary action by pre-fetching remote data into local memory before it is strictly needed for computation. When a task is suspended waiting for remote data, the system proactively initiates data transfer operations in advance. This allows the computation to proceed as soon as the data arrives, rather than waiting passively, thereby reducing the effective communication latency impact on overall processing productivity.
2Productivity
If the number of concurrent tasks is increased to utilize computation resources, then computational resource utilization improves, but communication latency acts as a bottleneck reducing scalability
Solution Approach 1:
The patent ensures continuity of useful action by maintaining multiple worker threads that continuously execute tasks without idle waiting periods. When one worker thread is blocked waiting for remote data, other threads continue processing their ready queues. The system also implements continuous pre-fetching of data in the background, ensuring that computational resources remain actively utilized rather than idle, thereby maintaining high productivity while overcoming communication latency bottlenecks through parallel continuous operation.
Data Source
AI summary
Techniques are provided for latency-hiding context management for concurrent distributed tasks. A plurality of task objects is processed, including a first task object corresponding to a first task that includes access to first data residing on a remote machine. A first access request is added to a request buffer. A first task reference identifying the first task object is added to a companion buffer. A request message including the request buffer is sent to the remote machine. A response message is received, including first response data responsive to the first access request. For each response of one or more responses of the response message, the response is read from the response message, a next task reference is read from the companion buffer, and a next task corresponding to the next task reference is continued based on the response. The first task is identified and continued.