FIFO Instruction Reordering for Latency Reduction
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Solution Overview
Problem
Existing processors with long latency, high throughput hardware units face challenges in optimizing and scheduling instructions due to hardware FIFOs imposing ordering constraints, making it difficult to reduce latency in executing complex workloads like machine learning computations.
Innovation Solution
A method that reorders FIFO instructions at compile time by determining path length metrics and generating a new order for independent groups of FIFO instructions to reduce latency, allowing for improved scheduling and execution efficiency across multiple hardware processors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If hardware FIFOs are used to interface with long latency hardware units, then data flow control is simplified, but instruction scheduling flexibility is reduced due to ordering constraints
Solution Approach 1:
The patent segments FIFO instructions into independent groups based on whether they produce data needed by subsequent instructions. This segmentation allows flexible scheduling of independent groups while maintaining FIFO ordering within each group, resolving the contradiction between simple data flow control and complex instruction scheduling.
Solution Approach 2:
The patent introduces dynamic scheduling where the order of independent FIFO instruction groups can be adjusted at runtime based on data dependencies and hardware availability. This dynamic approach maintains the simplicity of FIFO data flow control while providing the flexibility needed for optimized instruction scheduling.
2Device complexity
If FIFO instructions are executed in fixed order, then hardware implementation is simplified, but execution latency increases due to unnecessary waiting
Solution Approach 1:
The patent performs preliminary analysis at compile time to identify independent groups of FIFO instructions and determine their execution order. This preliminary action allows the hardware to execute instructions in an optimized sequence that reduces waiting time while maintaining the simplicity of FIFO hardware implementation.
Solution Approach 2:
The patent changes the execution parameter from fixed order to dynamic order based on data dependencies. By analyzing which FIFO instructions produce data needed by subsequent instructions, the system adjusts execution timing to minimize latency while keeping hardware implementation simple.
3Productivity
If compilers optimize instruction scheduling, then execution efficiency improves, but complexity of handling hardware FIFO constraints increases
Solution Approach 1:
The patent extracts the scheduling complexity from the compiler by pre-computing independent groups and their optimal execution orders. This extraction allows the compiler to handle FIFO constraints more effectively by focusing only on grouping instructions rather than managing complex ordering constraints during compilation.
Solution Approach 2:
The patent introduces an intermediary representation that separates FIFO instructions into independent groups based on data dependencies. This intermediary structure simplifies compiler handling by providing a clear framework for scheduling while maintaining the necessary hardware FIFO constraints.
4Productivity
If hardware resources are allocated to threads with long latency instructions, then computation can proceed, but resource utilization decreases due to waiting
Solution Approach 1:
The patent implements dynamic resource allocation where hardware resources can be reallocated between threads based on the completion status of long latency instructions. By monitoring which FIFO instruction groups have completed, the system dynamically adjusts resource distribution to maximize utilization while maintaining computation throughput.
Solution Approach 2:
The patent enables discarding of hardware resource allocation to threads waiting for long latency instructions and recovering those resources for other productive work. This is achieved by identifying when FIFO instruction groups complete and reallocating resources accordingly, reducing waste while maintaining overall productivity.
Data Source
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AI summary
Methods, systems, and apparatus for scheduling first-in-first-out (FIFO) instructions are described. In one aspect, a method includes receiving data representing code of a program to be executed by a processing unit having hardware processors. For each of one or more hardware processors, an order of independent groups of FIFO instructions for execution by the hardware processor is identified in the data representing the code. For each independent group of FIFO instructions for execution by the hardware processor, a path length metric that represents how long it will take to reach an end of the program from the independent group of FIFO instructions is determined. A new order of the independent groups of FIFO instructions for execution by the hardware processor is generated based at least on the path length metric for each independent group of FIFO instructions for execution by the hardware processor.