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[[CUDA]] (and General-Purpose Graphics Processing Unit programming in general) is rapidly becoming a mainstay of high-performance computing. As CUDA and OpenCL move off of the workstation, and into the server -- off of the console, and into the cluster -- the security of these systems will become critical parts of the associated [http://en.wikipedia.org/wiki/Trusted_computing_base trusted computing base]. Even ignoring the issue of multiuser security, the properties of isolation and (to a lesser extent) confidentiality are important for debugging, profiling and reproducibility. I've authored cudafucker and associated tools to investigate the security properties -- primarily the means and parameters of memory protection, and the division of protection between soft- and hardware -- of [[CUDA]] on NVIDIA hardware since the G80 architecture. | [[CUDA]] (and [http://en.wikipedia.org/wiki/GPGPU General-Purpose Graphics Processing Unit] programming in general) is rapidly becoming a mainstay of high-performance computing. As CUDA and OpenCL move off of the workstation, and into the server -- off of the console, and into the cluster -- the security of these systems will become critical parts of the associated [http://en.wikipedia.org/wiki/Trusted_computing_base trusted computing base]. Even ignoring the issue of multiuser security, the properties of isolation and (to a lesser extent) confidentiality are important for debugging, profiling and reproducibility. I've authored cudafucker and associated tools to investigate the security properties -- primarily the means and parameters of memory protection, and the division of protection between soft- and hardware -- of [[CUDA]] on NVIDIA hardware since the G80 architecture. | ||
Revision as of 09:40, 11 April 2010
CUDA (and General-Purpose Graphics Processing Unit programming in general) is rapidly becoming a mainstay of high-performance computing. As CUDA and OpenCL move off of the workstation, and into the server -- off of the console, and into the cluster -- the security of these systems will become critical parts of the associated trusted computing base. Even ignoring the issue of multiuser security, the properties of isolation and (to a lesser extent) confidentiality are important for debugging, profiling and reproducibility. I've authored cudafucker and associated tools to investigate the security properties -- primarily the means and parameters of memory protection, and the division of protection between soft- and hardware -- of CUDA on NVIDIA hardware since the G80 architecture.
