Content Compute Processor Architecture for Reconfigurable Hardware Execution
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Solution Overview
Problem
Existing microprocessor architectures face limitations such as von-Neumann instruction bottlenecks, inflexibility due to pre-defined hardware structures, high power consumption, and inefficiencies in data movement, leading to poor compute data throughput and low instructions per cycle (IPC), while FPGAs suffer from complexity in configuration and reconfigurability issues, making them difficult to use for custom accelerators.
Innovation Solution
A macroprocessor architecture that integrates configurable CPU-pipelines, allowing user-defined functions to be programmed and dynamically altered, with a Syn-Compiler tool that converts high-level language applications into hardware instructions, facilitating content computing and optimizing performance and power usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If pre-defined hardware structures are used in microprocessors, then manufacturing is simplified and reliability is improved, but flexibility and adaptability deteriorate
Solution Approach 1:
The patent implements dynamically reconfigurable hardware structures that can change their configuration at runtime. The interconnect fabric allows routing paths to be dynamically altered, and logic blocks can be reconfigured to perform different functions, enabling the system to adapt to varying computational requirements without physical reconfiguration.
Solution Approach 2:
The patent creates universal hardware components that can perform multiple functions. The reconfigurable logic blocks and interconnect fabric enable the same physical structure to serve different computational purposes, allowing a single processor to handle diverse workloads including custom accelerators for AI, data processing, and other specialized tasks.
2Productivity
If von-Neumann architecture is used, then ease of manufacture is improved, but compute data throughput deteriorates due to instruction bottleneck
Solution Approach 1:
The patent segments the data-path into multiple parallel execution pipelines that can simultaneously process different instructions. This segmentation allows the system to overcome the von-Neumann bottleneck by enabling multiple data streams to flow through separate execution units, thereby increasing overall compute throughput.
Solution Approach 2:
The patent introduces an intermediary instruction queue and buffer structures that decouple instruction fetching from execution. This intermediary layer allows instructions to be fetched, decoded, and prepared for execution in parallel with data retrieval, reducing the bottleneck effect and improving throughput.
3Adaptability or versatility
If FPGAs are used for custom accelerators, then adaptability is improved, but ease of operation deteriorates due to configuration complexity
Solution Approach 1:
The patent implements self-service mechanisms where the system automatically manages hardware configuration based on software instructions. The compiler and runtime system handle the complexity of configuring reconfigurable logic blocks, translating high-level code into appropriate hardware configurations without requiring manual intervention from the user.
Solution Approach 2:
The patent introduces software intermediaries including a specialized compiler and runtime management layer that bridge the gap between high-level programming and hardware configuration. These intermediaries automatically generate and manage the complex configuration data required for reconfigurable hardware, making the system easy to operate while maintaining high adaptability.
4Productivity
If microprocessors are used, then ease of operation is improved, but power consumption increases and IPC deteriorates
Solution Approach 1:
The patent applies local quality by creating specialized hardware units optimized for specific computational tasks. Instead of using general-purpose microprocessor instructions for all operations, the system employs dedicated logic blocks and execution units that perform specific functions more efficiently, thereby increasing IPC and reducing the power required per instruction.
Solution Approach 2:
The patent replaces the mechanical instruction execution mechanism of microprocessors with direct hardware implementation of computational functions. By compiling code into hardware configurations rather than sequential instruction execution, the system achieves higher throughput and lower power consumption for compute-intensive tasks.
Data Source
AI summary
Software tools, tools flows and software infrastructure to extract content and execute extracted content in hardware (termed content-computing) from a high-level language description of an application software program is disclosed. A software program for content-computing comprises: a high-level logic synthesis software to convert an identified content in an application program to a synthesized hardware image; and a language compiler software to instantiate the content customized instruction to execute in a configurable hardware unit programmed to the synthesized hardware image. A software tools flow to generate executable instructions in an application software program comprises a combined high level logic synthesis software and language compiler software to: identify an application software program content that is targeted for hardware implementation as a hardware function in a configurable hardware unit that comprises configuration memory; generate a synthesized gate-level netlist of the targeted hardware function; generate a bit-stream of configuration memory to program the targeted hardware function in the configurable hardware unit; and generate a compiled hardware instruction for a processor unit to execute the instruction in the configured hardware function.