A large, fast instruction window for tolerating cache misses
ISCA '02 Proceedings of the 29th annual international symposium on Computer architecture
Speculative lock elision: enabling highly concurrent multithreaded execution
Proceedings of the 34th annual ACM/IEEE international symposium on Microarchitecture
Runahead Execution: An Alternative to Very Large Instruction Windows for Out-of-Order Processors
HPCA '03 Proceedings of the 9th International Symposium on High-Performance Computer Architecture
Scalable Hardware Memory Disambiguation for High ILP Processors
Proceedings of the 36th annual IEEE/ACM International Symposium on Microarchitecture
Checkpoint Processing and Recovery: Towards Scalable Large Instruction Window Processors
Proceedings of the 36th annual IEEE/ACM International Symposium on Microarchitecture
Reducing Design Complexity of the Load/Store Queue
Proceedings of the 36th annual IEEE/ACM International Symposium on Microarchitecture
Memory Ordering: A Value-Based Approach
Proceedings of the 31st annual international symposium on Computer architecture
ASPLOS XI Proceedings of the 11th international conference on Architectural support for programming languages and operating systems
Scalable Load and Store Processing in Latency Tolerant Processors
Proceedings of the 32nd annual international symposium on Computer Architecture
Store Vulnerability Window (SVW): Re-Execution Filtering for Enhanced Load Optimization
Proceedings of the 32nd annual international symposium on Computer Architecture
Out-of-Order Commit Processors
HPCA '04 Proceedings of the 10th International Symposium on High Performance Computer Architecture
Dual-Core Execution: Building a Highly Scalable Single-Thread Instruction Window
Proceedings of the 14th International Conference on Parallel Architectures and Compilation Techniques
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New load and store processing algorithms let memory-latency-tolerant architectures sustain thousands of in-flight instructions without scaling cycle-critical fully-associative load and store queues. These algorithms rely on redoing some stores after fetching cache miss data from memory (to fix memory dependences). Doing so provides better power and area characteristics than constantly enforcing memory dependences among a several loads and stores, many of which have unknown addresses.