Mixed Scalar Vector Operations in Multi-threaded Computing
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Solution Overview
Problem
Current GPU architectures are inefficient for scalar operations due to their Single Instruction Multiple Threads (SIMT) processing, where only one core executes scalar instructions, leading to idle cores and inefficiency in handling both scalar and parallel computing tasks.
Innovation Solution
A processor design that includes a sequencer with scalar and vector instruction decoders, capable of distinguishing between scalar and vector instructions, and a processing element array with multiple Arithmetic Logic Units (ALUs) to execute scalar operations separately and vector operations in parallel, optimizing thread-level parallelism.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a SIMT processor executes scalar instructions using only one core, then scalar operations can be performed, but all other cores remain idle causing low productivity
Solution Approach 1:
The processor is segmented into two distinct execution paths: a scalar execution path with a single core for scalar operations, and a parallel execution path with multiple cores for vector operations. The instruction dispatcher segments incoming instructions and routes them to the appropriate execution path based on instruction type, ensuring that scalar instructions go to the single core while vector instructions utilize the parallel core array.
Solution Approach 2:
The processor achieves multi-functionality by enabling the same hardware structure to handle both scalar and vector operations efficiently. The instruction dispatcher and register file serve both execution paths, while the parallel core array can be dynamically configured to handle vector operations, making the processor adaptable to different computational workloads without requiring separate dedicated hardware for each operation type.
2Productivity
If a SIMT processor is designed for massive parallel computing, then vector operations are efficient, but scalar operations become inefficient due to idle cores
Solution Approach 1:
The instruction dispatcher acts as an intermediary between the instruction stream and the execution units. It analyzes incoming instructions, determines whether they are scalar or vector operations, and routes them to the appropriate execution path. This mediator component enables the processor to seamlessly switch between scalar and vector execution modes without requiring complex reconfiguration or sacrificing efficiency in either operation type.
3Productivity
If all cores execute vector instructions in parallel, then thread-level parallelism is maximized, but scalar instructions cannot be executed efficiently
Solution Approach 1:
The processor employs dynamic instruction routing where the execution path is determined at runtime based on the instruction type. The instruction dispatcher dynamically analyzes each incoming instruction and directs it to the appropriate execution unit - scalar instructions to the single core and vector instructions to the parallel core array. This dynamic adaptation allows the processor to maintain high thread-level parallelism for vector operations while efficiently handling scalar operations as needed.
Data Source
AI summary
Processors, systems and methods are provided for thread level parallel processing. A processor may include a sequencer configured to: decode instructions that include scalar instructions and vector instructions, execute decoded scalar instructions, and package decoded vector instructions as configurations. The processor may further include a plurality of columns of vector processing units coupled to the sequencer. The plurality of columns of vector processing units may include a plurality of processing elements (PEs) and each of the PEs may include a plurality of Arithmetic Logic Units (ALUs). The sequencer may be configured to send the configurations to the plurality of columns of vector processing units.