Percentile-Based Memory Performance Control for Heterogeneous Systems
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Solution Overview
Problem
Current computer systems face challenges in managing memory performance requirements for applications, particularly in heterogeneous memory architectures, where existing solutions lack adaptability and dynamicity, leading to inefficient data placement and performance optimization across different memory tiers.
Innovation Solution
A processor apparatus and method that provide a percentile-based memory performance requirement interface, allowing for flexible control of memory performance by allocating resources based on specific requirements, and a memory performance controller that monitors and adjusts data placement across different memory tiers to meet these requirements, using bitmap information and telemetry data to optimize memory access.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If existing memory management solutions are used in heterogeneous memory architectures, then basic memory operations can be performed, but adaptability and dynamicity are insufficient leading to inefficient data placement and performance optimization
Solution Approach 1:
The patent implements dynamic memory management by continuously monitoring memory access patterns and performance metrics, then automatically adjusting data placement decisions. The system transitions from static to dynamic control by adapting memory allocation strategies based on real-time workload characteristics and performance requirements, enabling optimal data placement across heterogeneous memory tiers.
Solution Approach 2:
The system changes key parameters including memory allocation policies, data placement decisions, and performance thresholds based on monitored workload characteristics. By dynamically adjusting these parameters according to actual system state and performance requirements, the system achieves both adaptability to different workloads and optimized performance across diverse memory architectures.
2Reliability
If memory resources are allocated to meet specific performance requirements, then application performance can be guaranteed, but resource utilization efficiency may be reduced
Solution Approach 1:
The patent applies local quality by providing differentiated memory service levels to different data structures based on their specific performance requirements. Critical data structures receive guaranteed performance through reserved memory resources and priority allocation, while non-critical data uses available capacity efficiently. This localized quality of service approach ensures performance requirements are met for essential operations while maintaining overall resource utilization efficiency.
Solution Approach 2:
The system implements partial resource reservation by allocating memory resources proportionally to performance requirements rather than fully reserving capacity. This allows the system to guarantee minimum performance levels while leaving excess resources available for dynamic allocation to other workloads, thereby balancing reliability with resource utilization efficiency.
3Productivity
If data structures are moved across memory tiers to optimize performance, then memory performance requirements can be met, but system complexity increases
Solution Approach 1:
The patent implements self-service by enabling the memory management system to automatically monitor its own performance metrics, make placement decisions, and execute data migration operations without external intervention. The system services itself by detecting performance bottlenecks and autonomously optimizing data placement across memory tiers, thereby achieving improved memory performance while managing complexity through automation rather than manual control mechanisms.
Solution Approach 2:
The system employs feedback mechanisms by continuously monitoring memory access patterns, performance metrics, and workload characteristics, then using this information to guide data placement decisions. The feedback loop enables the system to adapt to changing conditions and optimize performance dynamically, managing complexity through information-driven automation rather than predetermined complex control logic.
Data Source
AI summary
Examples relate to a processor apparatus, device, method and computer program, to a memory performance controller apparatus, device, method and computer program and to a memory controller apparatus, device, method and computer program. The processor apparatus comprises interface circuitry for communicating with other components of the computer system. The processing circuitry is configured to provide an interface for controlling a memory performance requirement of a data structure stored within a memory of the computer system. The memory performance requirement is a percentile-based memory performance requirement comprising at least a first memory performance requirement valid for a first portion of access operations and a second memory performance requirement valid for a second portion of access operations. The processing circuitry is configured to control a memory system of the computer system to provide the memory performance indicated by the memory performance requirement in response to an instruction obtained via the interface for controlling the memory performance requirement of the data structure.