Partitioned GPU Cache with Dynamic Overfetch and Pre-Eviction
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Solution Overview
Problem
Conventional cache structures in graphics processing units (GPUs) are inefficient, leading to suboptimal performance in processing graphics data due to inefficiencies in cache partitioning, dynamic overfetching, and cache scrubbing/pre-eviction mechanisms.
Innovation Solution
Implementing a partitioning mechanism for large GPU caches, dynamic overfetching of cache lines, and cache scrubbing/pre-eviction processes to optimize cache utilization and reduce latency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional cache structures are used in GPUs, then the cache structure is simple, but cache efficiency is low and processing performance is suboptimal
Solution Approach 1:
The cache is divided into multiple partitions or ways, with each partition capable of storing different types of data (e.g., texture data, vertex data, fragment data). This segmentation allows simultaneous access to different data types, improving cache efficiency and processing performance without requiring a complete redesign of the cache structure.
Solution Approach 2:
The cache structure implements dynamic allocation and management of cache lines, where cache lines can be dynamically assigned to different partitions based on data type and access patterns. This dynamic approach optimizes cache utilization for varying workloads while maintaining a relatively simple underlying cache structure.
2Productivity
If cache size is increased to improve performance, then more data can be cached, but cache access latency increases and memory bandwidth is reduced
Solution Approach 1:
The large cache is segmented into multiple smaller partitions that can be accessed independently. This allows the cache system to serve multiple data requests simultaneously from different partitions, effectively increasing throughput without proportionally increasing access latency for individual cache lines.
Solution Approach 2:
While one cache partition is being accessed, other partitions can simultaneously perform cache operations such as filling, evicting, or scrubbing data. This continuous utilization of cache resources ensures that the increased cache capacity does not result in idle time or increased latency for active operations.
3Productivity
If dynamic overfetching is implemented to improve cache utilization, then more data is pre-loaded into cache, but memory bandwidth is consumed and cache capacity is used inefficiently
Solution Approach 1:
Different regions or partitions of the cache are optimized for different types of data access patterns. Some partitions are configured for spatial prefetching while others are optimized for temporal locality, allowing selective overfetching only in regions where it provides benefit without wasting memory bandwidth in regions where it would be inefficient.
Solution Approach 2:
The cache system monitors access patterns and dynamically adjusts overfetching behavior based on actual data usage. When data is accessed, the system learns from this feedback and selectively pre-loads similar or related data into appropriate cache partitions, avoiding unnecessary memory bandwidth consumption while maintaining high cache utilization.
4Reliability
If cache scrubbing and pre-eviction mechanisms are implemented to maintain data integrity, then data accuracy is improved, but processing time is lost and cache efficiency is reduced
Solution Approach 1:
The cache is divided into partitions with different scrubbing and eviction policies based on data type and importance. Critical data in certain partitions receives more frequent scrubbing and pre-eviction attention, while less critical data in other partitions uses reduced scrubbing frequency, maintaining data integrity where needed while minimizing processing time overhead.
Solution Approach 2:
Cache scrubbing and pre-eviction operations are performed continuously in the background on idle cache partitions without interrupting active data access operations. This allows data integrity maintenance to occur concurrently with normal cache operations, preventing loss of processing time for legitimate cache accesses.
Data Source
AI summary
Embodiments are generally directed to cache structure and utilization. An embodiment of an apparatus includes one or more processors including a graphics processor; a memory for storage of data for processing by the one or more processors; and a cache to cache data from the memory; wherein the apparatus is to provide for dynamic overfetching of cache lines for the cache, including receiving a read request and accessing the cache for the requested data, and upon a miss in the cache, overfetching data from memory or a higher level cache in addition to fetching the requested data, wherein the overfetching of data is based at least in part on a current overfetch boundary, and provides for data is to be prefetched extending to the current overfetch boundary.