Unified Virtual Memory for CPU-GPU Transfer Reduction
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Solution Overview
Problem
Existing memory management in heterogeneous computing systems, such as those involving CPUs and GPUs, is inefficient due to the need for manual management of memory transfers and the risk of out-of-memory exceptions, which can be exacerbated by limited GPU memory capacity and unnecessary data migrations.
Innovation Solution
Implementing a Unified Virtual Memory (UVM) system that manages physical memory transparently across processors, including a UVM driver to handle GPU memory pressure and avoid redundant data transfers by marking data as discardable and delaying remapping until necessary.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual memory management is implemented for each processor, then memory transfer control is precise, but programming complexity increases quadratically with the number of processors
Solution Approach 1:
A UVM driver acts as an intermediary layer between applications and multiple processors (CPU, GPU, etc.), providing unified virtual memory management. The driver handles memory allocation, mapping, and transfer operations centrally, eliminating the need for programmers to manually manage memory for each processor. This intermediary abstracts the complexity of heterogeneous memory systems while maintaining precise control over memory transfers.
2Reliability
If data is migrated to different devices for memory coherency, then memory consistency is maintained, but processing time is wasted when data is immediately overwritten
Solution Approach 1:
The system performs preliminary actions by tracking data validity and migration status before actual memory operations. The UVM driver monitors which data has been migrated and maintains metadata about data location and validity. This preliminary tracking prevents unnecessary migration operations by checking data status beforehand, avoiding the waste of migrating data that will be immediately overwritten.
3Reliability
If GPU memory capacity is increased to handle larger computations, then out-of-memory exceptions are reduced, but system cost and resource requirements increase
Solution Approach 1:
The unified virtual memory system enables memory to serve multiple functions across different processors. GPU memory can be used for GPU computations, while the same physical memory can be accessed by the CPU when needed. This multi-functionality allows the system to handle larger computational workloads without proportionally increasing GPU memory capacity, as memory can be dynamically shared and allocated based on current computational needs.
Data Source
AI summary
Apparatuses, systems, and techniques for memory management are disclosed. In at least one embodiment, memory management is provided for a heterogenous system, for example, a system including a CPU and a GPU, in which redundant or unnecessary memory transfers are reduced.