Multivalue Reductions Serial Initial Parallel Subsequent Register Spaces
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional parallel processing devices face a bottleneck in performing multivalue reductions, which are typically done serially, limiting throughput in high-demand applications like audio generation neural networks that require rapid computation of multiple values.
Innovation Solution
The system employs parallel processing hardware to compute multivalue reductions by performing initial reductions in serial across multiple register spaces and then moving data into a single register space for subsequent parallel reductions, allowing for the computation of multiple final values simultaneously.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If multivalue reductions are performed using conventional serial methods, then the implementation is simple, but the processing speed and throughput are limited
Solution Approach 1:
The patent divides the multivalue reduction problem into multiple single-value reduction subproblems. Each thread block handles one value reduction by processing elements from multiple register spaces in parallel, then combining results. This segmentation allows the system to leverage existing efficient single-value reduction hardware while achieving multivalue functionality through coordinated parallel execution across multiple thread blocks.
2Productivity
If multiple single-value reductions are performed serially, then the implementation is straightforward, but the throughput is bottlenecked
Solution Approach 1:
The patent performs preliminary organization of data by having each thread block load and reduce elements from different register spaces into shared memory before the final combination step. Thread blocks prepare their partial results in advance, storing reduced values in shared memory registers. This preliminary action enables the final parallel combination phase to proceed efficiently without data access bottlenecks, significantly improving overall throughput.
3Loss of time
If parallel processing capabilities are fully utilized, then the computation time is reduced, but the device complexity increases
Solution Approach 1:
The patent introduces a new dimension of parallelism by organizing thread blocks to process different values simultaneously while each block handles multiple elements in parallel. The invention creates a two-dimensional parallel execution model: one dimension for element-wise parallelism within thread blocks, and another dimension for value-wise parallelism across thread blocks. This dimensional approach maximizes hardware utilization without requiring complex coordination mechanisms.
Data Source
AI summary
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for computing a multivalue reduction using a parallel processing device. One of the methods includes performing a parallel M-value reduction by parallel processing units of a parallel processing device. A plurality of initial reductions are performed in serial, each initial reduction operating on data in a different respective register space of at least M register spaces. Data is moved from the M register spaces so that all results from the plurality of initial reductions are in a same first register space. One or more subsequent reductions are performed in parallel to compute M final values, each subsequent reduction operating only on data in the first register space.