Processor Operand Metadata for Speculative Execution Efficiency
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Solution Overview
Problem
Modern computer processors face inefficiencies in exploiting instruction-level parallelism, particularly in techniques that employ speculation, which can lead to wasted computational bandwidth and power, and struggle to effectively utilize vectorization in loops.
Innovation Solution
A computer processor design that stores operand data values alongside meta-data as unitary operand data elements, allowing hardware operations to jointly handle these data types, enabling efficient processing of speculable and non-speculable operations, including error handling and operand management through meta-data associated with scalar and vector operands.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If speculative execution is used to exploit instruction-level parallelism, then execution speed is improved, but computational bandwidth and power are wasted on unnecessary operations
Solution Approach 1:
The processor performs preliminary actions by speculatively executing instructions before knowing whether they are needed, then uses metadata tagging to identify and discard unnecessary results. This allows the processor to maintain high execution speed while avoiding waste through intelligent result validation and disposal.
Solution Approach 2:
The system discards computational results that are determined to be unnecessary through metadata analysis. By attaching metadata to operands and results, the processor can efficiently identify and discard wasted computation products without affecting the correctness of needed results, thus reducing energy waste while maintaining speed.
2Productivity
If complex circuitry is added to enable discarding unneeded execution results, then speculation efficiency is improved, but device complexity increases
Solution Approach 1:
Metadata serves as an intermediary between the speculative execution engine and the result validation mechanism. Instead of complex circuitry directly analyzing and discarding results, metadata acts as a simplified mediator that carries information about operand validity, type, and dependencies, enabling efficient result disposal with minimal additional hardware complexity.
Solution Approach 2:
The patent replaces complex mechanical/circuitry-based result validation with a metadata-based information system. Rather than using elaborate circuit networks to determine which results to discard, the system uses tagged metadata that can be processed through simpler logical operations, reducing hardware complexity while improving speculation efficiency.
3Productivity
If traditional techniques are used for vectorization of loops, then instruction-level parallelism is exploited, but effectiveness in utilizing vectorization is limited
Solution Approach 1:
The metadata system provides universal support for multiple operand types (scalars, vectors, structured data) and multiple loop types (while-loops, counting loops, search loops). By attaching type information and metadata to operands rather than requiring separate handling mechanisms for each case, the processor achieves effective vectorization across diverse loop structures with a unified approach.
Solution Approach 2:
The system changes parameters by attaching metadata that describes operand characteristics such as type, size, and vectorization potential. This metadata enables the processor to dynamically adapt its execution strategy based on the actual parameters of the data being processed, improving vectorization effectiveness without requiring fixed, specialized circuitry for each loop type.
Data Source
AI summary
A computer processor is provided that employs a plurality of operand storage elements that store operand data values and associated meta-data as unitary operand data elements as well as at least one functional unit that performs operations that produce and access the unitary operand data elements stored in the plurality of operand storage elements. The meta-data associated with a given operand data value as part of a unitary operand data element can specify type of the unitary operand data element (e.g., vector or scalar), elemental width and floating-point error flags. The meta-data can also be used to define special operand data values (e.g., Not-a-Result and None). The meta-data is useful in optimizing execution, such as in speculation and vectorized SIMD operations. The computer processor can also support a number of particular vector operations that are useful in optimizing execution of vectorized SIMD operations.