2 citations · 4 across the 6 of their papers we have counts for
6 papers
BB-ML: Basic Block Performance Prediction using Machine Learning Techniques
Hamdy Abdelkhalik, Shamminuj Aktar, Yehia Arafa +8
Recent years have seen the adoption of Machine Learning (ML) techniques to predict the performance of large-scale applications, mostly at a coarse level. In contrast, we propose to…
Analytical Cost Metrics : Days of Future Past
Nirmal Prajapati, Sanjay Rajopadhye, Hristo Djidjev
As we move towards the exascale era, the new architectures must be capable of running the massive computational problems efficiently. Scientists and researchers are continuously in…
PCOT: Cache Oblivious Tiling of Polyhedral Programs
Waruna Ranasinghe, Nirmal Prajapati, Tomofumi Yuki +1
This paper studies two variants of tiling: iteration space tiling (or loop blocking) and cache-oblivious methods that recursively split the iteration space with divide-and-conquer.…
Scheduling and Tiling Reductions on Realistic Machines
Nirmal Prajapati
Computations, where the number of results is much smaller than the input data and are produced through some sort of accumulation, are called Reductions. Reductions appear in many s…
Accelerator Codesign as Non-Linear Optimization
Nirmal Prajapati, Sanjay Rajopadhye, Hristo Djidjev +3
We propose an optimization approach for determining both hardware and software parameters for the efficient implementation of a (family of) applications called dense stencil comput…
Hybrid Static/Dynamic Schedules for Tiled Polyhedral Programs
Tian Jin, Nirmal Prajapati, Waruna Ranasinghe +4
Polyhedral compilers perform optimizations such as tiling and parallelization; when doing both, they usually generate code that executes "barrier-synchronized wavefronts" of tiles.…