Vector Index Instruction for Dynamic Parallelism Adaptation
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Solution Overview
Problem
Existing vector processors face challenges in vectorizing loops due to loop-carried data dependencies and memory-address aliasing, which limits the extent of parallelism that can be exploited, requiring manual recoding and extensive effort, and thus have not gained widespread adoption for general-purpose applications.
Innovation Solution
A processor architecture that executes a vector instruction by receiving a start value and an increment value, optionally with a predicate vector, generating a result vector where elements are set to the start value plus a product of the increment multiplied by the number of active elements to the left, allowing dynamic switching between scalar and vector execution based on runtime conditions, enabling parallelism without requiring complete parallelism determination at compile-time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If existing vector processors are used to vectorize loops, then parallelism can be exploited, but loop-carried data dependencies and memory-address aliasing limit the extent of parallelism
Solution Approach 1:
The patent implements dynamic switching between scalar and vector execution modes based on runtime conditions. The processor can adaptively select whether to execute instructions in scalar mode or vector mode depending on the presence of loop-carried dependencies and memory aliasing, allowing the extent of parallelism to be dynamically adjusted rather than fixed at compile time
Solution Approach 2:
The invention changes the execution parameter from fixed scalar or fixed vector to a dynamic parameter that can switch between modes. By introducing a mechanism to detect runtime conditions and adjust the execution mode accordingly, the system can optimize the degree of parallelism exploitation based on actual loop characteristics
2Productivity
If manual recoding is performed to enable vectorization, then parallelism can be achieved, but extensive effort is required
Solution Approach 1:
The processor architecture performs self-service by automatically detecting loop-carried dependencies and memory aliasing conditions, and autonomously switching between scalar and vector execution modes. This eliminates the need for manual recoding or extensive compiler intervention, as the system self-adapts to exploit parallelism where safe
3Productivity
If complete parallelism determination is done at compile-time, then vectorization can be achieved, but runtime adaptability is lost
Solution Approach 1:
The patent implements dynamic mode switching that allows the processor to adapt execution strategy at runtime. Instead of determining parallelism completely at compile-time, the system uses runtime detection of loop characteristics to dynamically select between scalar and vector execution, maintaining both vectorization capability and runtime adaptability
Data Source
AI summary
The described embodiments include a processor that executes a vector instruction. The processor starts by receiving a start value and an increment value, and optionally receiving a predicate vector with N elements as inputs. The processor then executes the vector instruction. Executing the vector instruction causes the processor to generate a result vector. When generating the result vector, if the predicate vector is received, for each element in the result vector for which a corresponding element of the predicate vector is active, otherwise, for each element in the result vector, the processor sets the element in the result vector equal to the start value plus a product of the increment value multiplied by a specified number of elements to the left of the element in the result vector.