Modeling Application Performance under Multi-Instance (Multi-Stream) Execution Scenarios

Multi-stream execution is a technique in GPUs that allows multiple operations/kernels from the same program to effectively use GPUs without explicitly stating the affinity of threads to the cores. Several recent optimizations in Machine Learning (ML) algorithms leverage multi-stream execution. While performance modeling of ML applications is well studied under single-stream execution, performance models of novel ML applications under multi-stream execution is lacking.

Automatic Optical Character Recognition Preprocessing for Custom Gameplay Text

Computer Games are one of the key use cases of graphics cards of AMD. To ensure highest quality and performance, extensive testing of graphics hardware and software is required. However, much of this gameplay testing is manual and requires significant efforts due to varying styles in games and their versions. In this context, an open challenge lies in the difficult to automatically pre-process multiple heavily styled and color instances of text that appear in various games which current requires manual tuning.