Thread-Agnostic Load Store Buffer for Out-of-Order Execution
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Solution Overview
Problem
Current processor architectures face inefficiencies in handling multiple threads due to the need for context switching, which results in high overhead and complexity, especially when fine-grained parallelism is required, and existing solutions do not effectively manage speculative execution and memory consistency.
Innovation Solution
Implementing an out-of-order instruction scheduling process that allows instructions to issue as soon as processor resources are available, using a load/store queue to maintain in-order execution semantics and recover from speculative errors, and splitting load and store instructions into macro/microinstructions for earlier optimization and recovery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If hardware duplicates all architecture state elements for each supported thread, then context switch is eliminated for hardware-supported threads, but area, power and complexity increase significantly
Solution Approach 1:
The architecture state is segmented into thread-specific components (program counter, thread ID) and shared components (register file, load store buffer). Instead of duplicating the entire architecture state for each thread, only the essential thread-identifying elements are replicated, while the bulk of the state sharing is maintained through a unified structure.
Solution Approach 2:
The load store buffer is designed to be thread-agnostic, serving multiple threads simultaneously without requiring thread-specific instances. The buffer handles load and store operations from any thread using a unified data structure, eliminating the need for per-thread buffer duplications while maintaining correct memory ordering semantics.
2Loss of time
If hardware supports a limited number of threads with duplicate context state, then context switch overhead is reduced for those threads, but threads exceeding hardware support still require context switching
Solution Approach 1:
The architecture dynamically manages thread contexts by allowing any thread to be actively executed without being limited to a fixed set of hardware-supported threads. The load store buffer and register file can serve any thread context that is currently active, enabling flexible thread scheduling and eliminating context switches for threads within the active set.
Solution Approach 2:
The load store buffer automatically handles thread-specific memory operations without requiring thread identification or context-specific buffer instances. The buffer self-adapts to serve any thread's load and store operations through a unified interface, eliminating the need for hardware to pre-configure support for specific thread counts.
3Reliability
If load store buffer is made thread-aware with separate buffers per thread, then thread-specific memory ordering is maintained, but area and complexity increase
Solution Approach 1:
Separate load buffers and store buffers from different threads are merged into unified structures. The load buffer consolidates load operations from multiple threads, and the store buffer consolidates store operations, with each entry tagged by thread ID. This merging reduces total buffer area while maintaining the ability to enforce memory ordering within each thread through the thread ID tagging mechanism.
4Productivity
If context switch is performed frequently for fine-grained parallelism, then more threads can be executed, but overhead increases significantly
Solution Approach 1:
The architecture prepares for thread switching in advance by maintaining a ready state for multiple threads in the load store buffer and register file. When a thread switch is needed, the new thread's context is already positioned and ready to be activated, eliminating the need for costly context initialization and reducing the overhead of frequent context switches for fine-grained parallelism.
Data Source
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AI summary
In a processor, a thread agnostic unified store queue and a unified load queue method for out of order loads in a memory consistency model using shared memory resources. The method includes implementing a memory resource that can be accessed by a plurality of asynchronous cores, wherein the plurality of cores share a unified store queue and a unified load queue; and implementing an access mask that functions by tracking which words of a cache line are accessed via a load, wherein the cache line includes the memory resource, wherein the load sets a mask bit within the access mask when accessing a word of the cache line, and wherein the mask bit blocks accesses from other loads from a plurality of cores. The method further includes checking the access mask upon execution of subsequent stores from the plurality of cores to the cache line, wherein stores from different threads can forward to loads of different threads while still maintaining in order memory consistency semantics; and causing a miss prediction when a subsequent store to the portion of the cache line sees a prior mark from a load in the access mask, wherein the subsequent store will signal a load queue entry corresponding to that load by using a tracker register and a thread ID register.