gem5-gpu: A Heterogeneous CPU-GPU Simulator

Runtime specialization for heterogeneous CPU-GPU platforms

Cache optimization for CPU - GPU heterogeneous processors ∗

Microprocessors combining CPU and GPU cores using a common last-level cache pose new challenges to cache management algorithms. Since GPU cores feature much higher data access rates than CPU cores, the majority of the available cache space will be used by GPU applications, leaving only very limited cache capacity for CPU applications, which may be disadvantageous for overall system performance....

CPU and/or GPU: Revisiting the GPU Vs. CPU Myth

Parallel computing using accelerators has gained widespread research attention in the past few years. In particular, using GPUs for general purpose computing has brought forth several success stories with respect to time taken, cost, power, and other metrics. However, accelerator based computing has significantly relegated the role of CPUs in computation. As CPUs evolve and also offer matching ...

A Hybrid GPU-CPU Renderer

In this paper we present a hybrid rendering approach that generates fast real time images of a scene by the GPU and then progressively improves quality by selective ray tracing. The GPU solution is used to guide the ray tracing towards error prone areas. We describe the interplay between these two passes for the generation of high quality hard and soft shadows, anti-aliasing, and reflections an...

GPU-to-CPU Callbacks

We present GPU-to-CPU callbacks, a new mechanism and abstraction for GPUs that offers them more independence in a hetero-ion for GPUs that offers them more independence in a heterogeneous computing environment. Specifically, we provide a method for GPUs to issue callback requests to the CPU. These requests serve as a tool for ease-of-use, future proofing of code, and new functionality. We class...