In this work, we demonstrate a system that allows texture memory on multiple GPUs to be virtualized in a manner that is both scalable and transparent to the programmer. Our system is built using a directory-based shared memory abstraction to allow texture memory to be distributed while staying consistent. We use texture pages as our basic memory block and discuss the data structures, threading model, and consistency mechanisms necessary to implement a paging system in a multi-GPU environment. The system is demand-driven, and pages will only be loaded into the texture memory of a GPU that makes a request. The main contribution of this work is the identification of the mechanisms required to implement our abstraction, as well as the discussio...
<p>Global memory, local memory, constant memory, and texture memory are all no GPU card and outside ...
In this dissertation, we explore multiple designs for a Distributed Transactional Memory framework f...
GPUs are being widely used to accelerate different workloads and multi-GPU systems can provide highe...
In this paper we present a consistent, distributed, shared memory system for GPU texture memory. Thi...
Video games and simulators commonly use very detailed textures, whose cumulative size is often large...
Texture mapping has been a fundamental feature for commodity graphics hardware. However, a key chall...
The texture-based volume rendering is a memory-intensive algorithm. Its performance relies heavily o...
Traditional graphics hardware architectures implement what we call the push architecture for texture...
International audienceModern games and applications use large amounts of texture data; the number an...
GPU-based computing systems have become a widely accepted solution for the high-performance-computin...
The performance of hardware-based interactive rendering systems is often constrained by polygon fil...
General-purpose computing on GPUs has become more accessible due to features such as shared virtual ...
Abstract: This work presents a distributed image-order volume rendering approach for scalable high-r...
The Graphics Processing Unit (GPU) has become a mainstream computing platform for a wide range of ap...
Advances in virtualization technology have enabled multiple virtual machines (VMs) to share resource...
<p>Global memory, local memory, constant memory, and texture memory are all no GPU card and outside ...
In this dissertation, we explore multiple designs for a Distributed Transactional Memory framework f...
GPUs are being widely used to accelerate different workloads and multi-GPU systems can provide highe...
In this paper we present a consistent, distributed, shared memory system for GPU texture memory. Thi...
Video games and simulators commonly use very detailed textures, whose cumulative size is often large...
Texture mapping has been a fundamental feature for commodity graphics hardware. However, a key chall...
The texture-based volume rendering is a memory-intensive algorithm. Its performance relies heavily o...
Traditional graphics hardware architectures implement what we call the push architecture for texture...
International audienceModern games and applications use large amounts of texture data; the number an...
GPU-based computing systems have become a widely accepted solution for the high-performance-computin...
The performance of hardware-based interactive rendering systems is often constrained by polygon fil...
General-purpose computing on GPUs has become more accessible due to features such as shared virtual ...
Abstract: This work presents a distributed image-order volume rendering approach for scalable high-r...
The Graphics Processing Unit (GPU) has become a mainstream computing platform for a wide range of ap...
Advances in virtualization technology have enabled multiple virtual machines (VMs) to share resource...
<p>Global memory, local memory, constant memory, and texture memory are all no GPU card and outside ...
In this dissertation, we explore multiple designs for a Distributed Transactional Memory framework f...
GPUs are being widely used to accelerate different workloads and multi-GPU systems can provide highe...