Distributed Compute Tiles for Asynchronous Accelerator Offloading
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Solution Overview
Problem
Existing data processing systems face inefficiencies in handling computationally-intensive tasks, particularly those requiring specialized operations like machine learning, due to the limitations of general-purpose CPUs and the overhead associated with centralized control of hardware accelerators.
Innovation Solution
A system comprising a cluster of compute tiles, each with a tile CPU and a hardware accelerator, allows for asynchronous task offloading and decentralized control, reducing overhead and improving performance through parallel processing and efficient resource allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a centralized control architecture is used to manage hardware accelerators, then system coordination is simplified, but control overhead and latency increase
Solution Approach 1:
The system divides the centralized control architecture into distributed compute tiles, where each tile contains its own CPU and hardware accelerator. This segmentation eliminates the need for centralized coordination overhead while maintaining system-wide cooperation through defined communication interfaces and protocols.
Solution Approach 2:
The patent transitions from a single-level centralized control hierarchy to a multi-dimensional distributed architecture where control is embedded at the tile level. This dimensional change allows parallel decision-making across multiple tiles simultaneously, reducing the temporal overhead associated with centralized sequential control.
2Device complexity
If general-purpose CPUs are used for all processing tasks, then system simplicity is maintained, but processing performance for specialized operations deteriorates
Solution Approach 1:
The patent merges general-purpose CPU functionality with specialized hardware accelerator capabilities within each compute tile. This combination allows the system to maintain the programming flexibility of CPUs while simultaneously achieving the high-performance specialized processing of dedicated hardware, resolving the trade-off between simplicity and performance.
Solution Approach 2:
Each compute tile is designed as a universal processing unit that can execute both general-purpose instructions on its CPU and specialized accelerated operations on its hardware accelerator. This multi-functionality allows a single tile architecture to handle diverse workloads without requiring separate specialized systems.
3Adaptability or versatility
If multiple hardware accelerators are managed centrally, then resource allocation is centralized, but resource competition and overhead increase
Solution Approach 1:
The patent segments the hardware accelerator resources into dedicated units within each compute tile, eliminating resource competition between tiles. Each tile's accelerator is locally managed by its own CPU, allowing independent resource allocation decisions without centralized coordination overhead or inter-tile resource conflicts.
Solution Approach 2:
Each compute tile operates as a self-sufficient unit where the local CPU directly manages and allocates its associated hardware accelerator resources without external intervention. This self-service capability reduces the overhead of centralized resource management while improving response time for resource allocation decisions.
Data Source
AI summary
An apparatus comprises a plurality of compute tiles coupled via a tile cluster interconnect; each compute tile comprising: a tile central processing unit (CPU); and a hardware accelerator configured to perform, asynchronously with respect to operations performed by processing circuitry of the tile CPU, a delegated task offloaded to the hardware accelerator by the tile CPU.