Managing performance vs. accuracy trade-offs with loop perforation
S Sidiroglou-Douskos, S Misailovic… - Proceedings of the 19th …, 2011 - dl.acm.org
Many modern computations (such as video and audio encoders, Monte Carlo simulations,
and machine learning algorithms) are designed to trade off accuracy in return for increased …
and machine learning algorithms) are designed to trade off accuracy in return for increased …
Using code perforation to improve performance, reduce energy consumption, and respond to failures
Many modern computations (such as video and audio encoders, Monte Carlo simulations,
and machine learning algorithms) are designed to trade off accuracy in return for increased …
and machine learning algorithms) are designed to trade off accuracy in return for increased …
Iterative optimization in the polyhedral model: Part I, one-dimensional time
Emerging microprocessors offer unprecedented parallel computing capabilities and deeper
memory hierarchies, increasing the importance of loop transformations in optimizing …
memory hierarchies, increasing the importance of loop transformations in optimizing …
Iterative optimization in the polyhedral model: Part II, multidimensional time
High-level loop optimizations are necessary to achieve good performance over a wide
variety of processors. Their performance impact can be significant because they involve in …
variety of processors. Their performance impact can be significant because they involve in …
Taming hardware event samples for FDO compilation
Feedback-directed optimization (FDO) is effective in improving application runtime
performance, but has not been widely adopted due to the tedious dual-compilation model …
performance, but has not been widely adopted due to the tedious dual-compilation model …
Predictive modeling in a polyhedral optimization space
High-level program optimizations, such as loop transformations, are critical for high
performance on multi-core targets. However, complex sequences of loop transformations …
performance on multi-core targets. However, complex sequences of loop transformations …
Using graph-based program characterization for predictive modeling
Using machine learning has proven effective at choosing the right set of optimizations for a
particular program. For machine learning techniques to be most effective, compiler writers …
particular program. For machine learning techniques to be most effective, compiler writers …
A compiler approach to fast hardware design space exploration in FPGA-based systems
The current practice of mapping computations to custom hardware implementations requires
programmers to assume the role of hardware designers. In tuning the performance of their …
programmers to assume the role of hardware designers. In tuning the performance of their …
Learning with differentiable pertubed optimizers
Abstract Machine learning pipelines often rely on optimizers procedures to make discrete
decisions (eg, sorting, picking closest neighbors, or shortest paths). Although these discrete …
decisions (eg, sorting, picking closest neighbors, or shortest paths). Although these discrete …
The privatizing doall test: A run-time technique for doall loop identification and array privatization
L Rauchwerger, D Padua - … of the 8th International Conference on …, 1994 - dl.acm.org
Current parallelizing compilers cannot identify a significant fraction of fully parallel loops
because they have complex or statically insufficiently defined access patterns. For this …
because they have complex or statically insufficiently defined access patterns. For this …