Ultra Large Instruction Matrix for Parallel Execution
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Solution Overview
Problem
Current computer architectures face challenges in improving performance without relying on frequency scaling and massive explicit software parallelization, as they struggle to efficiently execute large numbers of instructions in a short latency pipeline.
Innovation Solution
The Ultra Large Instruction Matrix (ULIM) architecture allows for the execution of a matrix of instructions that includes both parallel and dependent operations, enabling massive parallelism by scheduling fixed-size instruction matrices as groups of parallel and dependent instructions, which can be executed in a single processor pipeline with optimized timing, power, and area efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If frequency scaling is used to improve performance, then throughput is improved, but it hits a power wall making further improvements difficult
Solution Approach 1:
The patent segments instructions into a matrix format with multiple rows and columns, where each row represents a set of instructions that can execute in parallel. This segmentation allows the processor to execute multiple instructions simultaneously without increasing frequency, thereby improving throughput while avoiding the power consumption issues associated with frequency scaling.
Solution Approach 2:
The patent introduces a two-dimensional instruction matrix structure that adds a new dimension to instruction execution. Instead of executing instructions sequentially in a single dimension, the matrix format enables parallel execution across multiple rows and columns, achieving improved throughput without relying on frequency scaling and its associated power wall.
2Productivity
If massive explicit software parallelization is expressed to increase throughput, then productivity is improved, but device complexity increases
Solution Approach 1:
The patent implements a self-service approach where the hardware architecture automatically manages parallel execution of instructions in the matrix format. The processor autonomously schedules and executes instructions across different rows and columns without requiring complex software parallelization, thereby improving throughput while keeping software complexity manageable.
Solution Approach 2:
The patent changes the fundamental parameter of instruction organization from traditional linear sequences to a matrix format with explicit row and column dimensions. This parameter change enables the hardware to naturally handle parallel execution, improving throughput without transferring the complexity burden to the software level.
3Productivity
If traditional instruction execution is used, then device complexity is low, but throughput is limited and latency is high
Solution Approach 1:
The patent segments instructions into a matrix structure with multiple rows and columns, enabling parallel execution of instructions within the same row. This segmentation reduces the time required to execute all instructions by performing them simultaneously, thereby reducing latency while maintaining relatively simple device architecture.
Solution Approach 2:
The patent enables continuous execution of instructions through the matrix format, where multiple instructions can be executed in parallel without idle waiting time. This continuity of useful action improves throughput and reduces the overall execution time (latency) compared to traditional sequential execution, without significantly increasing device complexity.
Data Source
AI summary
A matrix of execution blocks form a set of rows and columns. The rows support parallel execution of instructions and the columns support execution of dependent instructions. The matrix of execution blocks process a single block of instructions specifying parallel and dependent instructions.