Dynamic Data Conversion for Sparse Formats and Network Throughput

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Solution Overview

Problem

Existing collective computing systems are limited by static sparse representations and precision formats, which restrict the types of computing nodes and switch circuitries that can be used and limit network bandwidth.

Innovation Solution

Incorporating conversion circuitry in computing nodes and switch circuitries to dynamically convert data signals between different sparse representations and precision formats, allowing for greater flexibility and compatibility among various computing elements.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If a static sparse representation and precision format are used to ensure compatibility across all computing nodes and switch circuitries, then system reliability is improved, but adaptability and network bandwidth are limited

Engineering Contradiction:

ImprovecompatibilityVSAvoiddesign flexibility

Core Design Contradiction:

ReliabilityVSAdaptability or versatility

Solution Approach 1:

The patent implements dynamic conversion circuitry that can adaptively transform data between different sparse representations and precision formats in real-time. This allows the system to dynamically adjust data formats based on the specific capabilities of computing nodes and switch circuitries, resolving the contradiction between maintaining compatibility and enabling design flexibility.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The conversion circuitry acts as an intermediary between data sources and processing elements with different format requirements. It translates data into appropriate formats for the receiving component, enabling heterogeneous computing nodes and switch circuitries to work together reliably while maintaining adaptability in format selection.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Reliability

If a static sparse representation and precision format are used, then compatibility is ensured, but network bandwidth is limited

Engineering Contradiction:

ImprovecompatibilityVSAvoidnetwork bandwidth

Core Design Contradiction:

ReliabilityVSProductivity

Solution Approach 1:

The system changes data representation parameters (sparse representation patterns and precision levels) dynamically based on the processing capabilities of computing nodes and the requirements of the application. This allows optimization of network bandwidth by using more compact representations when appropriate while maintaining compatibility through conversion capabilities.

Inventive Principle:

Principle #35Parameter changes

3Adaptability or versatility

If diverse computing nodes and switch circuitries are used to increase design flexibility, then adaptability is improved, but compatibility issues arise

Engineering Contradiction:

Improvedesign flexibilityVSAvoidcompatibility

Core Design Contradiction:

Adaptability or versatilityVSReliability

Solution Approach 1:

The conversion circuitry provides universal compatibility by supporting multiple sparse representations and precision formats within a single system. This enables diverse computing nodes and switch circuitries with different capabilities to be integrated into the same network, achieving both design flexibility and compatibility.

Inventive Principle:

Principle #6Universality (Multi-functionality)

4Adaptability or versatility

If dynamic conversion between different sparse representations and precision formats is implemented, then adaptability and network throughput are improved, but device complexity increases

Engineering Contradiction:

Improvedesign flexibilityVSAvoidconversion circuitry

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The conversion functionality is segmented into dedicated conversion circuitry components that can be selectively implemented in computing nodes and/or switch circuitries. This modular approach allows the system to gain adaptability benefits while distributing the complexity burden across multiple components rather than requiring every component to handle all conversion types.

Inventive Principle:

Principle #1Segmentation

Data Source

PatentUS20250150520A1Dynamic data conversion for network computer systems

Publication Date: 2025.05.08 XILINX INC

AI summary

A computing node for a computing system includes a processor, conversion circuitry, and routing circuitry. The processor generates a data signal based on a function of an application executed by the computing system. The data signal has a first precision format and a first sparse representation. The conversion circuitry receives the data signal from the processor and generate a converted data signal by at least one of converting the first precision format to a second precision format and converting the first sparse representation to a second sparse representation. The routing circuitry transmits the converted data signal to switch circuitry of the computing system.