Asynchronous Data Pipeline for GPU Memory Bottlenecks
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Solution Overview
Problem
Memory dependencies in parallel computing platforms, such as GPUs, lead to performance bottlenecks due to synchronization requirements for shared data, causing threads to wait and reducing parallel performance.
Innovation Solution
Implementing an asynchronous data movement pipeline that allows direct copying of data from global memory to shared memory without intermediate cache stages, reducing computational overhead and enabling concurrent execution of threads.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If data is copied through intermediate cache stages (L2 cache, L1 cache) before reaching shared memory, then data transfer reliability is maintained, but transfer speed decreases and computational overhead increases
Solution Approach 1:
The patent extracts and removes intermediate cache stages (L2 cache, L1 cache) from the data transfer path between global memory and shared memory. By taking out these intermediate components, the data transfer path is simplified to a direct connection, eliminating the complexity of multiple cache stages while maintaining data transfer reliability through alternative mechanisms.
Solution Approach 2:
The patent implements preliminary actions by pre-fetching data into shared memory before it is needed by threads, and by pre-synchronizing data dependencies. This allows threads to execute concurrently without waiting for data to propagate through intermediate caches, as the data is already prepared and available in shared memory when needed.
2Reliability
If threads synchronize to wait for data changes to propagate through memory, then data consistency is ensured, but parallel performance decreases due to execution stalls
Solution Approach 1:
The patent introduces shared memory as an intermediary between global memory and thread working data. Instead of threads directly depending on global memory changes that require synchronization, shared memory serves as a buffer that threads can access independently. Data is copied to shared memory in advance, allowing threads to proceed without synchronization stalls while maintaining consistency through the controlled data copy process.
Solution Approach 2:
The patent performs preliminary data copying to shared memory and preliminary synchronization of data dependencies before threads begin execution. This preliminary action ensures data consistency is established beforehand, allowing threads to execute in parallel without needing to synchronize during execution, thus maintaining both reliability and productivity.
3Loss of time
If intermediate cache stages are used for data transfer, then data availability is maintained, but computational overhead increases due to multiple memory access stages
Solution Approach 1:
The patent removes intermediate cache stages from the memory access architecture, simplifying the path from global memory to shared memory. This extraction eliminates the time loss associated with multiple cache access stages while reducing the overall complexity of the memory access architecture. Data is transferred directly to shared memory where threads can access it immediately.
Solution Approach 2:
The patent implements preliminary data transfer to shared memory before thread execution begins. This preliminary action ensures data is already available in shared memory when threads need it, eliminating waiting time during thread execution. The complexity of coordinated multi-stage caching is replaced with a simpler direct transfer mechanism that completes beforehand.
Data Source
AI summary
Apparatuses, systems, and techniques to parallelize operations in one or more programs with data copies from global memory to shared memory in each of the one or more programs. In at least one embodiment, a program performs operations on shared data and then asynchronously copies shared data to shared memory, and continues performing additional operations in parallel while the shared data is copied to shared memory until an indicator provided by an application programming interface to facilitate parallel computing, such as CUDA, informs said program that shared data has been copied to shared memory.