Tensor Parallel Group Topology for Low-Overhead Multi-Device AI Compute
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Solution Overview
Problem
Processing large tensors using a single processor is challenging due to computational inefficiencies and memory bottlenecks, necessitating improved methods for tensor operations.
Innovation Solution
A tensor parallel group is formed with multiple processing devices, each handling tensor tiles, and communication channels directly link devices within sets without internal coupling, allowing efficient parallel execution and reduced data sharing through methods like data reduction and gather processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a single processor is used to process large tensors, then the system structure is simple, but computational efficiency is low and memory bottlenecks occur
Solution Approach 1:
The patent divides a large tensor processing task into multiple segments, with each processing device handling a specific portion of the tensor (tensor tiles). The tensor is partitioned across multiple devices, allowing parallel computation of different tensor segments simultaneously, thereby improving computational efficiency while managing system complexity through structured division of labor
Solution Approach 2:
The patent introduces a new dimension of parallelism by organizing processing devices into multiple sets (first set and second set) with different communication patterns. This multi-dimensional organization allows simultaneous data gathering within sets and data reduction between sets, enabling efficient parallel tensor operations across multiple processing dimensions
2Productivity
If multiple processing devices are used for tensor operations, then computational efficiency improves, but communication overhead and data sharing requirements increase
Solution Approach 1:
The patent segments the tensor data and processing devices into distinct groups (first set and second set), where each segment processes specific tensor tiles. This segmentation reduces unnecessary communication by ensuring that each processing device only exchanges data with specific counterpart devices in other segments, minimizing overall communication overhead while maintaining parallel computational efficiency
Solution Approach 2:
The patent introduces communication channels as intermediaries that facilitate efficient data exchange between processing device sets. These dedicated communication channels act as mediators that optimize data transfer by establishing direct communication paths between specific devices in the first set and second set, reducing the need for broadcast communications and minimizing energy consumption
3Speed
If processing devices are densely connected for data sharing, then data access is fast, but bandwidth consumption and communication complexity increase
Solution Approach 1:
The patent segments the communication topology into distinct first and second sets of processing devices, with structured communication channels between them. This segmentation creates a manageable communication structure where each device has defined communication partners, reducing overall system complexity while maintaining fast data access through dedicated communication paths
Solution Approach 2:
The patent implements local quality by optimizing communication within specific device sets and between corresponding sets. Each processing device is configured with tailored communication capabilities directed at specific counterpart devices, rather than universal connectivity. This localized communication approach reduces bandwidth consumption and simplifies the overall communication topology while preserving fast data access where needed
Data Source
AI summary
A tensor parallel group including multiple processing devices separated into a first set of two or more of the processing devices and a second set of two or more of the processing devices. The tensor parallel group may also include multiple communication channels to directly communicatively couple every processing device in the first set of the processing devices with every processing device in the second set of the processing devices without communicatively coupling any of the processing devices in the same set of the processing devices. In these and other embodiments, the processing devices may be configured such that each of the processing devices may be able to communicate with any of the other of the processing devices through at most one other of the processing devices.