Transactional Memory Commit Arbitrator Ordering
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
In transactional memory systems, programmers face challenges in ensuring the correct commit order of transactions, which is crucial for avoiding conflicts and ensuring the correctness of parallel programs, especially when executing loops in parallel, as the existing systems lack a guaranteed commit order, leading to potential unexpected results due to side effects and order dependencies.
Innovation Solution
A transactional memory system is enhanced with a feature to specify a pre-determined commit order for transactions, using a commit arbitrator to enforce total or partial ordering, ensuring that transactions commit in a predictable manner and manage conflicts based on this order, thereby transforming sequential loops into parallel loops that preserve the original input-to-output mapping.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If transactions are executed in parallel without guaranteed commit order, then productivity is improved through parallel execution, but reliability deteriorates due to unpredictable commit ordering and potential side effects
Solution Approach 1:
The patent applies preliminary action by assigning commit order numbers to transactions before they execute. This pre-determined ordering information is embedded in each transaction, allowing the system to maintain predictable commit sequencing even while transactions execute in parallel, thus ensuring reliability without sacrificing productivity
Solution Approach 2:
The commit order number acts as an intermediary mechanism between parallel transaction execution and final commit ordering. By introducing this intermediate ordering identifier, the system can decouple the execution phase from the commit phase, allowing parallel execution while guaranteeing correct commit sequencing through the mediator's arbitration
2Reliability
If a pre-determined commit order is enforced for all transactions, then reliability is improved through predictable commit sequencing, but device complexity increases due to additional ordering management mechanisms
Solution Approach 1:
The patent applies local quality by making commit ordering optional rather than universal. The system can selectively enforce commit order based on transaction characteristics or programmer annotations, applying complexity only where needed while allowing simple transactions to execute with minimal overhead, thus improving reliability without unnecessarily increasing overall system complexity
Solution Approach 2:
The system changes the parameter of commit ordering from a binary state (ordered/unordered) to a configurable spectrum. By allowing transactions to carry optional commit order numbers and enabling selective enforcement, the system can adjust the degree of ordering applied based on specific program requirements, balancing reliability needs against complexity costs
3Productivity
If sequential loops are parallelized without commit ordering, then productivity is improved through concurrent execution, but manufacturing precision deteriorates due to loss of original input-to-output mapping
Solution Approach 1:
The patent applies preliminary action by pre-assigning commit order numbers to loop iterations before parallel execution. This ensures that even though iterations execute concurrently, they will commit in the original sequential order, preserving the input-to-output mapping and maintaining manufacturing precision while achieving productivity gains through parallel execution
Solution Approach 2:
The system creates a logical copy of the sequential execution order through commit order numbers. While physical execution occurs in parallel, the commit phase reproduces the original sequential ordering, effectively copying the deterministic behavior of sequential execution into the parallel domain and preserving precision
Data Source
Figure 1
Figure 2
Figure 3
AI summary
Various technologies and techniques are disclosed for transforming a sequential loop into a parallel loop for use with a transactional memory system. Open ended and/or closed ended sequential loops can be transformed to parallel loops. For example, a section of code containing an original sequential loop is analyzed to determine a fixed number of iterations for the original sequential loop. The original sequential loop is transformed into a parallel loop that can generate transactions in an amount up to the fixed number of iterations. As another example, an open ended sequential loop can be transformed into a parallel loop that generates a separate transaction containing a respective work item for each iteration of a speculation pipeline. The parallel loop is then executed using the transactional memory system, with at least some of the separate transactions being executed on different threads.