Indexing External Memory in Reconfigurable Compute Fabric

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Solution Overview

Problem

Conventional computer architectures face performance and capacity constraints due to the time and energy required for data movement between processors and memory, limiting advancements beyond transistor scaling.

Innovation Solution

The implementation of memory-centric compute topologies, specifically compute-near-memory (CNM) systems, which integrate processors with memory or data storage components, utilizing hybrid threading processors and reconfigurable compute fabrics to facilitate low-latency operations through custom compute fabrics and programmable atomic units.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Quantity of substance

If data is stored in external memory and accessed via bus, then memory capacity is improved, but access time and energy consumption increase

Engineering Contradiction:
Improvememory capacityVSAvoiddata access time
Core Design Contradiction:
Quantity of substanceVSLoss of time

Solution Approach 1:

The patent segments memory into multiple banks (first bank, second bank, etc.) that can be accessed independently and simultaneously. Each compute element can access different memory banks in parallel, reducing the time penalty of large memory capacity while maintaining high data availability through spatial segmentation of the memory space.

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

The patent introduces a new dimension of parallelism by organizing memory access across multiple compute elements that can simultaneously access different memory locations. Instead of sequential access through a single bus, the system uses a mesh network topology where multiple data paths exist concurrently, transforming the access model from one-dimensional sequential to multi-dimensional parallel access.

Inventive Principle:
Principle #17Another dimension (Dimensionality change)

2Productivity

If data is moved between processors and memory, then computational capacity is improved, but energy consumption increases

Engineering Contradiction:
Improvecomputational capacityVSAvoidenergy consumption
Core Design Contradiction:
ProductivityVSUse of energy by moving object

Solution Approach 1:

The patent merges computation and memory access functions into an integrated architecture where compute elements are directly coupled to memory banks through a mesh network. This combination eliminates the need for separate data movement operations between distinct processor and memory units, reducing energy consumption while maintaining high computational capacity through tight integration of storage and processing functions.

Inventive Principle:
Principle #5Merging (Combining)

Solution Approach 2:

Each compute element can independently access memory banks without requiring centralized data movement control. The distributed architecture allows compute elements to self-service their data needs directly from local and remote memory banks through the mesh network, eliminating energy-intensive centralized data shuffling and reducing overall system energy consumption.

Inventive Principle:
Principle #25Self-service

3Device complexity

If conventional Von Neumann architecture is used, then system simplicity is maintained, but performance is constrained

Engineering Contradiction:
Improvesystem simplicityVSAvoidcomputing performance
Core Design Contradiction:
Device complexityVSProductivity

Solution Approach 1:

The patent implements a dynamically reconfigurable mesh network that can adapt its connectivity and data flow patterns based on computational requirements. The system transitions from the static, fixed data path of conventional Von Neumann architecture to a dynamic topology where compute elements and memory banks can communicate through multiple adaptable paths, enabling high performance while maintaining manageable complexity through systematic design.

Inventive Principle:
Principle #15Dynamics

Solution Approach 2:

The mesh network architecture provides universal connectivity where any compute element can access any memory bank through multiple possible paths. This multi-functional communication infrastructure replaces the specialized, single-purpose data bus of conventional architectures, delivering superior performance while maintaining system simplicity through a unified, scalable interconnection topology that handles diverse computational workloads.

Inventive Principle:
Principle #6Universality (Multi-functionality)

Data Source

PatentUS11704130B2Indexing external memory in a reconfigurable compute fabric
Publication Date: 2023.07.18 MICRON TECHNOLOGY INC
  • US11704130B2 patent drawing
  • US11704130B2 patent drawing
  • US11704130B2 patent drawing

AI summary

Various examples are directed to systems and methods in which a flow controller of a first synchronous flow may receive an instruction to execute a first loop using the first synchronous flow. The flow controller may determine a first iteration index for a first iteration of the first loop. The flow controller may send, to a first compute element of the first synchronous flow, a first synchronous message to initiate a first synchronous flow thread for executing the first iteration of the first loop. The first synchronous message may comprise the iteration index. The first compute element may execute an input/output operation at a first location of a first compute element memory indicated by the first iteration index.