Dynamic speculation and synchronization of data dependences
Proceedings of the 24th annual international symposium on Computer architecture
Memory dependence prediction using store sets
Proceedings of the 25th annual international symposium on Computer architecture
Dynamic memory disambiguation in the presence of out-of-order store issuing
Proceedings of the 32nd annual ACM/IEEE international symposium on Microarchitecture
The Alpha 21264 Microprocessor Architecture
ICCD '98 Proceedings of the International Conference on Computer Design
Automatic Generation of Microarchitecture Simulators
ICCL '98 Proceedings of the 1998 International Conference on Computer Languages
Instruction Based Memory Distance Analysis and its Application
Proceedings of the 14th International Conference on Parallel Architectures and Compilation Techniques
Feedback-directed memory disambiguation through store distance analysis
Proceedings of the 20th annual international conference on Supercomputing
Counting Dependence Predictors
ISCA '08 Proceedings of the 35th Annual International Symposium on Computer Architecture
| Hi-index | 0.00 |
Memory dependence prediction allows out-of-order issue processors to achieve high degrees of instruction level parallelism by issuing load instructions at the earliest time without causing a significant number of memory order violations. We present a simple mechanism which incorporates multiple speculation levels within the processor and classifies the load and the store instructions at run time to the appropriate speculation level. Each speculation level istermed as a color and the sets of load and store instructions are called color sets. We present how this mechanism can be incorporated into the issue logic of a conventional super-scalarprocessor and show that this simple mechanism can provide similar performance to that of more costly schemes resulting in reduced hardware complexity and cost. The performance of the technique is evaluated with respect to the store set algorithm.At very small table sizes, the color set approach provides up to 21% better performance than the store set algorithm for floating point Spec-95 benchmarks and up to 18% better performance for integer benchmarks using harmonic means.