A performance analysis framework for identifying potential benefits in GPGPU applications
Proceedings of the 17th ACM SIGPLAN symposium on Principles and Practice of Parallel Programming
Break down GPU execution time with an analytical method
Proceedings of the 2012 Workshop on Rapid Simulation and Performance Evaluation: Methods and Tools
Simultaneous branch and warp interweaving for sustained GPU performance
Proceedings of the 39th Annual International Symposium on Computer Architecture
Multi2Sim: a simulation framework for CPU-GPU computing
Proceedings of the 21st international conference on Parallel architectures and compilation techniques
TEAPOT: a toolset for evaluating performance, power and image quality on mobile graphics systems
Proceedings of the 27th international ACM conference on International conference on supercomputing
| Hi-index | 0.01 |
We present Barra, a simulator of Graphics Processing Units (GPU) tuned for general purpose processing (GPGPU). It is based on the UNISIM framework and it simulates the native instruction set of the Tesla architecture at the functional level. The inputs are CUDA executables produced by NVIDIA tools. No alterations are needed to perform simulations. As it uses parallelism, Barra generates detailed statistics on executions in about the time needed by CUDA to operate in emulation mode. We use it to understand and explore the micro-architecture design spaces of GPUs.