GPUs have evolved quite radically during the last ten years, providing

improvements in the areas of performance, power consumption, memory,

and programmability, increasing interest in them. This increase

in interest, especially in academic research into GPU architecture,

has led to the creation of the widely used GPGPU-Sim, a GPU simulator

for general purpose computation workloads. The simulation models

currently available for simulation are based on older architectures,

and as new GPU architectures have been introduced, GPGPU-Sim has not been

updated to model them.

This project attempts to model a more modern GPU, the Maxwell based

GeForce GTX Titan X. This is accomplished by modifying the existing

configuration files for one of the older simulation models. The

changes made to the configuration files include changing the GPU's

organization, updating the clock domains, and increasing cache and

memory sizes. To test the accuracy of the model, eleven GPGPU

programs, some having multiple kernels, were chosen to be executed by

the model and by the physical hardware, and compared using IPC as the

metric.

While for some of the kernels the model performed within 16% of the

GeForce GTX Titan X, there were an equal number of kernels for which

the model performed either much faster or much slower than the hardware.

It is suspected that the cases for which the model performed much faster

were ones in which either the hardware executed single precision instructions

as double precision instructions, or the hardware ran an entirely different

machine code for the same kernel than the model. The cases for which the model

performed much slower are suspected to be due to the fact that the Maxwell

memory subsystem cannot currently be accurately modeled in GPGPU-Sim.