Adaptive input-aware compilation for graphics engines

While graphics processing units (GPUs) provide low-cost and efficient platforms for accelerating high performance computations, the tedious process of performance tuning required to optimize applications is an obstacle to wider adoption of GPUs. In addition to the programmability challenges posed by GPU’s complex memory hierarchy and parallelism model, a well-known application design problem is target portability across different GPUs. However, even for a single GPU target, changing a program’s input characteristics can make an already-optimized implementation of a program perform poorly. In this work, we propose Adaptic, an adaptive input-aware compilation system to tackle this important, yet overlooked, input portability problem. Using this system, programmers develop their applications in a high-level streaming language and let Adaptic undertake the difficult task of input portable optimizations and code generation. Several input-aware optimizations are introduced to make ef�...

• Type: Journal
• Year: 2012
• Where: PLDI
• Authors: Mehrzad Samadi, Amir Hormati, Mojtaba Mehrara, Janghaeng Lee, Scott A. Mahlke
• Keywords: Memory Hierarchy, Performance Computations, PLDI 2012, Programming Languages, Programming Languages Processors