Block-Based Processor Architecture for Energy-Efficient Execution
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Solution Overview
Problem
Current processor architectures, such as superscalar out-of-order microarchitectures, face challenges in sustaining performance improvements due to complexity and resource intensity, particularly in register renaming, dataflow analysis, and misspeculation recovery, which hinders energy efficiency and area optimization.
Innovation Solution
The implementation of block-based processor architectures with explicit data graph execution (EDGE) ISA, which organizes instructions into blocks for atomic execution, reduces the need for complex architectural features like register renaming and misspeculation recovery, and uses hybrid dataflow execution to support high instruction-level parallelism and out-of-order execution with near in-order power efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If superscalar out-of-order microarchitectures are used to improve processor performance, then instruction-level parallelism is enhanced, but device complexity and resource intensity increase significantly
Solution Approach 1:
The processor architecture segments instructions into fixed-size blocks (e.g., 4 instructions per block) that are decoded and executed together. This block-based organization simplifies the control logic by eliminating the need for complex dynamic scheduling, register renaming, and speculation mechanisms while maintaining high instruction-level parallelism through block-level parallel execution.
Solution Approach 2:
The architecture changes the fundamental execution parameter from dynamic out-of-order execution of individual instructions to fixed-block atomic execution. This parameter change simplifies the control unit design, reduces hardware resources, and improves energy efficiency while maintaining productivity through optimized block scheduling and compilation techniques.
2Productivity
If complex architectural features like register renaming and misspeculation recovery are implemented to improve performance, then instruction throughput increases, but energy consumption increases
Solution Approach 1:
The architecture extracts and eliminates complex energy-consuming features such as register renaming, dynamic scheduling, and misspeculation recovery mechanisms. By removing these components, the design achieves lower energy consumption while maintaining high instruction throughput through simplified block-based execution and compilation optimizations.
Solution Approach 2:
The architecture uses simple, fixed-block instruction structures that can be rapidly decoded and executed without requiring complex hardware state management. This approach replaces expensive, complex architectural features with simpler, more energy-efficient mechanisms that achieve similar or better throughput for many workloads.
3Device complexity
If block-based processor architectures with atomic execution are used to simplify hardware, then device complexity is reduced, but flexibility in instruction ordering may be limited
Solution Approach 1:
The architecture performs instruction reordering and optimization during the compilation phase rather than requiring dynamic hardware reordering capabilities. The compiler analyzes dependencies and arranges instructions within blocks to maximize parallelism and efficiency, allowing the hardware to execute blocks atomically without complex reordering logic while still achieving high adaptability for different workloads.
Data Source
AI summary
Apparatus and methods are disclosed for controlling execution of memory access instructions in a block-based processor architecture using a hardware structure that generates a relative ordering of memory access instruction in an instruction block. In one example of the disclosed technology, a method of executing an instruction block having a plurality of memory load and/or memory store instructions includes decoding an instruction block encoding a plurality of memory access instructions and generating data indicating a relative order for executing the memory access instructions in the instruction block and scheduling operation of a portion of the instruction block based at least in part on the relative order data. In some examples, a store vector data register can store the generated relative ordering data for use in subsequent instances of the instruction block.