Cipherbase is a comprehensive database system that provides strong end-to-end data confidentiality through encryption. Cipherbase is based on a novel architecture that combines an industrial strength database engine (SQL Server) with lightweight processing over encrypted data that is performed in secure hardware. The overall architecture provides significant benefits over the state-of-the-art in terms of security, performance, and functionality.This paper presents a prototype of Cipherbase that uses FPGAs to provide secure processing and describes the system engineering details implemented to achieve competitive performance for transactional workloads. This includes hardware-software codesign issues (e.g. how to best offer parallelism), optimizations to hide the latency between the secure hardware and the main system, and techniques to cope with space inefficiencies. All these optimizations were carefully designed not to affect end-to-end data confidentiality. Our experiments with the TPC-C benchmark show that in the worst case when all data are strongly encrypted, Cipherbase achieves 40% of the throughput of plaintext SQL Server. In more realistic cases, if only critical data such as customer names are encrypted, the Cipherbase throughput is more than 90% of plaintext SQL Server.

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As technology advances, more and more issues need to be considered in the placement stage, e.g., wirelength, congestion, timing, coupling. It is very hard to consider all of them together at the same time. Thus it is good if we can optimize one cost function without affecting others. In this paper, we will study methods to optimize congestion in placement without inflicting degradations/violations in other objectives or constraint. We give a mathematical equation to predict the overflow within a region using a normal distribution approximation. According to experiments, this equation does give a good estimation of overflow. We used this equation to find the smallest regions which have enough routing resource to alleviate the congestion and propose the flexible expansion scheme in our multi-center congestion reduction (MC'R) algorithm. Experimental results show that generally there is a correlation between the amount of reduction in congestion and the amount of change made to the placement: the more we change the placement, the more reduction in congestion we will get. However, the flexible expansion scheme is very effective in helping us reduce congestion while make only little change to the placement. Comparing to the full expansion scheme (49% congestion reduction and 6.5% change in placement), the flexible expansion scheme together with MC'R algorithm can reduce congestion by almost the same amount (42%) with much less change made to the placement (1.8%).

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Modular multiplication of long integers is an important building block for cryptographic algorithms. Although several FPGA accelerators have been proposed for large modular multiplication, previous systems have been based on O(N 2 ) algorithms. In this paper, we present a Montgomery multiplier that incorporates the more efficient Karatsuba algorithm which is O(N (log 3/ log 2) ). This system is parameterizable to different bitwidths and makes excellent use of both embedded multipliers and fine-grained logic. The design has significantly lower LUT-delay product and multiplier-delay product compared with previous designs. Initial testing on a Virtex-6 FPGA showed that it is 60-190 times faster than an optimized multi-threaded software implementation running on an Intel Xeon 2.5 GHz CPU. The proposed multiplier system is also estimated to be 95-189 times more energy efficient than the software-based implementation. This high performance and energy efficiency makes it suitable for server-side applications running in a datacenter environment.