Collective Acceleration Unit Tree Structure for Low Latency Data Transfer
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Solution Overview
Problem
In distributed multi-processor systems, the overhead associated with data transfer and interconnect protocols hinders performance improvements, particularly in host-to-host communications, due to limitations in existing networking technologies and adapter overhead.
Innovation Solution
A collective acceleration unit (CAU) with a tree structure is introduced, which receives collective packets, maps tree identifiers to indexes, and performs operations using associated resources to facilitate efficient data distribution and collection among processor nodes, reducing latency and adapter overhead through optimized packet flow control and resource management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If traditional networking technologies and interconnect protocols are used for host-to-host communications, then system compatibility and ease of implementation are maintained, but communication latency increases and performance deteriorates
Solution Approach 1:
The patent extracts and removes the interconnect protocol overhead from the communication path by implementing direct processor-to-processor data transfer mechanisms. The collective communication operations are handled directly between processors without passing through traditional network interface cards or interconnect protocol layers, thereby eliminating the performance bottleneck while maintaining system compatibility through software abstraction.
Solution Approach 2:
The patent introduces a collective communication library as an intermediary layer that enables direct processor-to-processor communication. This mediator handles the complexity of collective operations (such as broadcast, reduce, and scatter) while presenting a simplified interface to applications, thereby reducing latency without requiring changes to the underlying hardware architecture.
2Productivity
If faster networking technologies and network switch fabrics are deployed, then host-to-host communication speed improves, but adapter overhead and interconnect complexity increase
Solution Approach 1:
The patent extracts the data transfer operation from the network adapter by implementing zero-copy techniques that allow processors to access remote memory directly without involving the network interface card. This eliminates adapter overhead and energy consumption associated with traditional networking stacks while maintaining high throughput through optimized memory access paths.
Solution Approach 2:
The patent enables processors to perform their own data transfer operations through direct memory access mechanisms. Instead of relying on network adapters to manage data movement, processors autonomously handle collective communication operations by directly accessing remote memory spaces, thereby eliminating adapter overhead while maintaining high productivity.
3Productivity
If collective operations are implemented through traditional software layers, then system compatibility is maintained, but performance and efficiency deteriorate due to overhead
Solution Approach 1:
The patent implements preliminary action by pre-configuring collective communication patterns and caching communication metadata before actual data transfer operations. The collective communication library pre-computes communication paths and prepares data structures in advance, thereby reducing runtime overhead and improving parallel application efficiency without sacrificing system compatibility.
Data Source
AI summary
A mechanism is provided in a collective acceleration unit for performing a collective operation to distribute or collect data among a plurality of participant nodes. The mechanism receives an input collective packet for a collective operation from a neighbor node within a collective tree. The input collective packet comprises a tree identifier and an input data field and wherein the collective tree comprises a plurality of sub trees. The mechanism maps the tree identifier to an index within the collective acceleration unit. The index identifies a portion of resources within the collective acceleration unit and is associated with a set of neighbor nodes in a given sub tree within the collective tree. For each neighbor node the collective acceleration unit stores destination information. The collective acceleration unit performs an operation on the input data field using the portion of resources to effect the collective operation.