Local Memory Disambiguation for Compute-Slice Data Consistency
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Solution Overview
Problem
As modern computing technologies increase in complexity and parallelism, maintaining memory semantics across multiple processor cores becomes a significant challenge, leading to potential data corruption and reduced performance due to processor stalling.
Innovation Solution
A parallel architecture with compute slices and local memory disambiguation units (LMDUs) is implemented, where each compute slice is coupled to a local memory disambiguation unit (LMDU) and a global memory disambiguation unit (GMDU) to ensure that each core has access to the most updated data by detecting and resolving address aliasing through memory operation tables (MOTs) and GMDUs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If parallelism is increased by adding more processor cores, then processing performance is improved, but memory system complexity and data consistency challenges worsen
Solution Approach 1:
The patent divides the memory disambiguation function into separate dedicated units (LDUs) that are integrated with each compute slice. Each LDU independently handles address aliasing detection and resolution for its associated compute slice, segmenting the global memory management task into localized units that operate autonomously.
Solution Approach 2:
The patent introduces load-store units (LDUs) as intermediary components between compute slices and the memory system. These LDUs act as mediators that detect address aliasing, resolve data dependencies, and manage memory access timing, thereby simplifying the overall memory system complexity while supporting parallel processing.
2Productivity
If parallel processing is increased, then compute power is improved, but processor stalling due to memory access conflicts increases
Solution Approach 1:
The patent performs address aliasing detection and data dependency analysis in advance during the instruction issue stage, before actual memory access occurs. The LDU predicts potential conflicts and prepares resolution strategies proactively, preventing processor stalling by ensuring data availability before compute operations require it.
Solution Approach 2:
The patent implements feedback mechanisms where the LDU continuously monitors memory access patterns, detects address aliasing conditions, and adjusts instruction scheduling and data forwarding dynamically. This feedback loop enables the system to respond to memory conflicts in real-time, minimizing processor stalling while maintaining high compute throughput.
3Productivity
If more parallel compute slices are added, then processing capability is improved, but ensuring data consistency across cores becomes more difficult
Solution Approach 1:
The LDU acts as an intermediary that ensures data consistency by detecting address aliasing between different compute slices and resolving dependencies before executing memory operations. This mediation prevents data inconsistency issues that would otherwise arise from parallel access to shared memory locations.
Solution Approach 2:
Each compute slice with its integrated LDU autonomously manages its own memory access consistency checks and dependency resolutions. The system achieves global data consistency through the cumulative effect of local self-service operations at each compute slice, eliminating the need for complex centralized coordination.
Data Source
AI summary
A processing unit is accessed, comprising compute slices, a control unit, local memory disambiguation units (LMDUs), and memory system. Each slice includes an execution unit and is coupled to successor and predecessor slices. Each slice is coupled to an LMDU. The control unit distributes a first slice task to a first slice coupled to a first LMDU. The first slice executes the first task. The task includes a load instruction including a load address. The first slice issues the load instruction to the first LMDU. The issuing saves load information in a memory operation table (MOT) within the LMDU. The LMDU detects, based on the MOT, address aliasing between the load address and a store address of a previous store instruction. The MOT forwards store information from the previous store instruction. The store information satisfies one or more bytes of data required for the load instruction.