High-Speed Single-Database PIR Implementation

In this HotPETs session we would like to present an implementation of a singledatabase Private Information Retrieval (PIR) scheme that can process a database at 2 Gbits/s using a commodity Graphics Processing Unit (GPU). This session will have three goals : – Dispel the idea that single-database PIR schemes are unusable because too expensive from a computational point of view – Provide a tool to do fast single-database PIR for higher-level applications and tests – Highlight that "Lattices + GPUs = Huge speedup" compared to number-theory schemes In order to do this we will first give a quick introduction to single-database PIR schemes and highlight the computational issues. Then after a one slide presentation of how GPUs can be used to do general purpose computations, we will present in a very schematic way the scheme implemented and why it is well adapted to GPUs. Finally, we will present a performance comparison over different database sizes with mean and variance values. One or two demos are possible if the organizers agree with them. IMPORTANT NOTE: Our implementation can be donwloaded from http://www.assembla.com/spaces/pir_gpgpu2008 Project members : Carlos Aguilar Melchor, Benoit Crespin, Philippe Gaborit, Vincent Jolivet and Pierre Rousseau (lead programmer) High-Speed Single-Database PIR Implementation IMPORTANT NOTE: Our implementation can be donwloaded from http://www.assembla.com/spaces/pir_gpgpu2008 Abstract. In this HotPETs session we would like to present an implementation of a singledatabase Private Information Retrieval (PIR) scheme that can process a database at 2 Gbits/s using a commodity Graphics Processing Unit (GPU). This session will have three goals : – Dispel the idea that single-database PIR schemes are unusable because too expensive from a computational point of view – Provide a tool to do fast single-database PIR for higher-level applications and tests – Highlight that "Lattices + GPUs = Huge speedup" compared to number-theory schemes In order to do this we will first give a quick introduction to single-database PIR schemes and highlight the computational issues. Then after a one slide presentation of how GPUs can be used to do general purpose computations, we will present in a very schematic way the scheme implemented and why it is well adapted to GPUs. Finally, we will present a performance comparison over different database sizes with mean and variance values. One or two demos are possible if the organizers agree with them. In this HotPETs session we would like to present an implementation of a singledatabase Private Information Retrieval (PIR) scheme that can process a database at 2 Gbits/s using a commodity Graphics Processing Unit (GPU). This session will have three goals : – Dispel the idea that single-database PIR schemes are unusable because too expensive from a computational point of view – Provide a tool to do fast single-database PIR for higher-level applications and tests – Highlight that "Lattices + GPUs = Huge speedup" compared to number-theory schemes In order to do this we will first give a quick introduction to single-database PIR schemes and highlight the computational issues. Then after a one slide presentation of how GPUs can be used to do general purpose computations, we will present in a very schematic way the scheme implemented and why it is well adapted to GPUs. Finally, we will present a performance comparison over different database sizes with mean and variance values. One or two demos are possible if the organizers agree with them.