Multi-Tile GPU Memory Mapping for Cross-Tile Access Detection
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Solution Overview
Problem
Current graphics processing units (GPUs) face challenges in efficiently managing memory vulnerabilities to soft errors, which can lead to data corruption and processing errors, and existing solutions for memory management in multi-GPU configurations are limited in scalability and performance.
Innovation Solution
A unified memory address space is implemented across multiple GPUs and processor memories, allowing for efficient data sharing and synchronization, and a distributed memory model is used to enable optimal page migration and communication between GPUs, leveraging a common virtual memory address space to access physical processor and GPU memories.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a unified memory address space is implemented across multiple GPUs, then data sharing and synchronization efficiency is improved, but memory management complexity increases
Solution Approach 1:
A page sharing table is introduced as an intermediary data structure to manage the unified memory address space across multiple GPUs. The page sharing table tracks which memory pages are shared between GPUs and maintains mapping information, allowing efficient data sharing without requiring complex direct coordination between GPU memory management units. This intermediary structure simplifies the overall memory management complexity while enabling unified address space functionality.
2Speed
If a distributed memory model is used for optimal page migration, then communication efficiency between GPUs is improved, but system complexity increases
Solution Approach 1:
The memory system implements dynamic page migration capabilities where memory pages can be automatically moved between different GPU local memories and system memory based on access patterns and workload requirements. The system dynamically adjusts the location of memory pages to optimize communication efficiency, with the page sharing table tracking the current location and status of each page. This dynamic approach improves communication speed while the automated management reduces the burden on system complexity.
3Reliability
If cross tile access detection is implemented, then memory vulnerability to soft errors is reduced, but detection overhead increases
Solution Approach 1:
The system performs preliminary detection of cross-tile memory access patterns by tracking which memory pages are marked as shared in the page sharing table before actual access occurs. When a memory access request is made, the system checks the page sharing table to determine if the accessed page is a shared cross-tile page, allowing for proactive error detection and handling. This preliminary action approach reduces vulnerability to soft errors by identifying at-risk accesses before they occur, while the efficient table lookup minimizes detection overhead.
Data Source
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AI summary
Multi-tile Memory Management for Detecting Cross Tile Access, Providing Multi-Tile Inference Scaling with multicasting of data via copy operation, and Providing Page Migration are disclosed herein. In one embodiment, a graphics processor for a multi-tile architecture includes a first graphics processing unit (GPU) having a memory and a memory controller, a second graphics processing unit (GPU) having a memory and a cross-GPU fabric to communicatively couple the first and second GPUs. The memory controller is configured to determine whether frequent cross tile memory accesses occur from the first GPU to the memory of the second GPU in the multi- GPU configuration and to send a message to initiate a data transfer mechanism when frequent cross tile memory accesses occur from the first GPU to the memory of the second GPU.