Text compression
Two-level adaptive training branch prediction
MICRO 24 Proceedings of the 24th annual international symposium on Microarchitecture
Improving the accuracy of dynamic branch prediction using branch correlation
ASPLOS V Proceedings of the fifth international conference on Architectural support for programming languages and operating systems
Improving the accuracy of static branch prediction using branch correlation
ASPLOS VI Proceedings of the sixth international conference on Architectural support for programming languages and operating systems
Streamlining data cache access with fast address calculation
ISCA '95 Proceedings of the 22nd annual international symposium on Computer architecture
Dynamic path-based branch correlation
Proceedings of the 28th annual international symposium on Microarchitecture
ISCA '96 Proceedings of the 23rd annual international symposium on Computer architecture
Analysis of branch prediction via data compression
Proceedings of the seventh international conference on Architectural support for programming languages and operating systems
Value locality and load value prediction
Proceedings of the seventh international conference on Architectural support for programming languages and operating systems
Examination of a memory access classification scheme for pointer-intensive and numeric programs
ICS '96 Proceedings of the 10th international conference on Supercomputing
Assigning confidence to conditional branch predictions
Proceedings of the 29th annual ACM/IEEE international symposium on Microarchitecture
Compiler synthesized dynamic branch prediction
Proceedings of the 29th annual ACM/IEEE international symposium on Microarchitecture
Exceeding the dataflow limit via value prediction
Proceedings of the 29th annual ACM/IEEE international symposium on Microarchitecture
The performance potential of data dependence speculation & collapsing
Proceedings of the 29th annual ACM/IEEE international symposium on Microarchitecture
Speculative execution via address prediction and data prefetching
ICS '97 Proceedings of the 11th international conference on Supercomputing
Dynamic speculation and synchronization of data dependences
Proceedings of the 24th annual international symposium on Computer architecture
Proceedings of the 24th annual international symposium on Computer architecture
Prefetching using Markov predictors
Proceedings of the 24th annual international symposium on Computer architecture
Target prediction for indirect jumps
Proceedings of the 24th annual international symposium on Computer architecture
MICRO 30 Proceedings of the 30th annual ACM/IEEE international symposium on Microarchitecture
The predictability of data values
MICRO 30 Proceedings of the 30th annual ACM/IEEE international symposium on Microarchitecture
Highly accurate data value prediction using hybrid predictors
MICRO 30 Proceedings of the 30th annual ACM/IEEE international symposium on Microarchitecture
Effective Hardware-Based Data Prefetching for High-Performance Processors
IEEE Transactions on Computers
An architectural alternative to optimizing compilers
ASPLOS I Proceedings of the first international symposium on Architectural support for programming languages and operating systems
A study of branch prediction strategies
ISCA '81 Proceedings of the 8th annual symposium on Computer Architecture
Information content of CPU memory referencing behavior
ISCA '77 Proceedings of the 4th annual symposium on Computer architecture
Caching Function Results: Faster Arithmetic by Avoiding Unnecessary Computation
Caching Function Results: Faster Arithmetic by Avoiding Unnecessary Computation
Proceedings of the 20th annual international conference on Supercomputing
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The predictability of data values is studied at a fundamental level. Two basic predictor models are defined: Computational predictors perform an operation on previous values to yield predicted next values. Examples we study are stride value prediction and last value prediction; Context-Based predictors match recent value history (context) with previous value history and predict values based entirely on previously observed patterns. To understand the potential of value prediction we perform simulations with unbounded prediction tables that are immediately updated using correct data values. Simulations of integer SPEC95 benchmarks show that data values can be highly predictable. Best performance is obtained with context-based predictors; overall prediction accuracies are between 56% and 92%. The context based predictor typically has an accuracy about 20% better than the computational predictors (last value and stride). Results with bounded tables suggest the feasibility of context-based predictors that approximate the performance with unbounded tables.