Dynamic Accumulator Allocation for GPU Thread Performance
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The limited number of accumulators available per thread in graphics processing units (GPUs) restricts performance for computationally intensive operations, as a fixed allocation can hinder efficient resource utilization and increase completion time.
Innovation Solution
Implementing a pool of registers that can be dynamically shared among threads, allowing threads to allocate or release registers as needed, with a compiler determining register allocation for code blocks and using instructions like ZeroAccSync to manage register availability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a fixed number of accumulators is allocated per thread, then the register allocation is simple and deterministic, but the performance for computationally intensive operations is restricted and completion time increases
Solution Approach 1:
The patent implements dynamic accumulator allocation where threads can request and release accumulators from a shared pool based on actual computational needs rather than being assigned a fixed number. The allocation mechanism transitions from static to dynamic, allowing the number of available accumulators per thread to change over time based on workload demands, thereby reducing completion time for intensive operations.
Solution Approach 2:
The system changes the parameter of accumulator availability from a fixed value to a variable that can change over time. By introducing a pool of shared accumulators that threads can dynamically access, the effective number of accumulators per thread becomes a function of time and workload, allowing optimization of performance without increasing the physical register count.
2Quantity of substance
If the physical accumulator array size is increased to provide more registers per thread, then the number of available registers increases, but the hardware resource consumption and device complexity increase
Solution Approach 1:
The patent merges the accumulator resources across threads by implementing a shared pool architecture. Instead of each thread having dedicated accumulators, the system combines accumulators into a common pool that can be dynamically allocated to multiple threads. This merging allows the system to provide more registers per thread when needed without proportionally increasing the total physical accumulator count.
Solution Approach 2:
The accumulator pool serves multiple threads simultaneously, making the accumulator resources universal rather than dedicated to single threads. The same physical accumulator can serve different threads at different times, increasing the effective quantity of registers available per thread without requiring a proportional increase in physical hardware resources.
3Adaptability or versatility
If accumulators are dynamically shared among threads, then the number of available registers per thread increases without expanding physical array, but the allocation management complexity increases
Solution Approach 1:
The patent introduces an intermediary allocation management system that mediates between threads and the accumulator pool. This intermediary layer handles the complexity of tracking which accumulators are available, allocating them to requesting threads, and managing their release. The intermediary abstracts the complexity from the threads themselves, allowing dynamic sharing while managing the overhead centrally.
Data Source
AI summary
A system that includes a graphics processing unit (GPU) that includes at least one processor and multiple registers. In some examples, based on execution of an instruction by at least one of the at least one processor to allocate a particular number of registers to a thread, assign the number of registers to the thread. In some examples, a compiler is to consider register demands for a code segment and number of available registers in determining a number of registers to allocate to the code segment.