In acute experiments on the anesthetized dog, partial or complete occlusion of the left innominate vein resulting in a rise of pressure in the venous territory into which the thoracic duct drains, commensurate with the venous pressure rise seen in congestive heart failure, reduces the flow of lymph in the thoracic duct. This decrease in thoracic duct lymph flow is due, at least partially, to the accumulation of lymph in the lymphatic system and possibly the intercellular spaces. The present acute experiments suggest the possibility that this factor may play a role in the genesis of the systemic edema of chronic congestive heart failure, although only chronic experiments now under way will permit definitive conclusions.

Today, pricing of derivates (particularly options) in financial institutions is a challenge. Besides the increasing complexity of the products, obtaining fair prices requires more realistic (and therefore complex) models of the underlying asset behavior. Not only due to the increasing costs, energy efficient and accurate pricing of these models becomes more and more important. In this paper we present -to the best of our knowledge -the first FPGA based accelerator for option pricing with the state-of-the-art Heston model. It is based on advanced Monte Carlo simulations. Compared to an 8-core Intel Xeon Server running at 3.07GHz, our hybrid FPGA-CPU-system saves 89% of the energy and provides around twice the speed. The same system reduces the energy consumption per simulation to around 40% of a fully-loaded Nvidia Tesla C2050 GPU. For a three-Virtex-5 chip only accelerator, we expect to achieve the same simulation speed as a Nvidia Tesla C2050 GPU, by consuming less than 3% of the energy at the same time.

The effects of arteriovenous fistulas of different magnitudes on cardiovascular dynamics were studied in anesthetized dogs. It was found that A-V fistula decreases mean systemic arterial pressure, effective systemic blood flow, total and pulmonary peripheral resistances, whereas it increases heart rate, total cardiac output, stroke volume, left atrial pressure, pulmonary arterial pressure, and systemic peripheral resistance. The magnitude of the above hemodynamic changes was essentially proportional to the size of the fistula. At equivalent increments in total cardiac output produced by A-V fistula and blood transfusion, the former condition causes a greater increase in pulmonary arterial pressure than the latter, although both conditions decrease the pulmonary peripheral resistance by the same degree. It was also found that, at equivalent left atrial pressures, left ventricular stroke work with A-V fistula was greater than that with blood transfusion.

Nowadays, high-speed computations are mandatory for financial and insurance institutes to survive in competition and to fulfill the regulatory reporting requirements that have just toughened over the last years. A majority of these computations are carried out on huge computing clusters, which are an ever increasing cost burden for the financial industry. There, state-of-the-art CPU and GPU architectures execute arithmetic operations with pre-defined precisions only, that may not meet the actual requirements for a specific application. Reconfigurable architectures like field programmable gate arrays (FPGAs) have a huge potential to accelerate financial simulations while consuming only very low energy by exploiting dedicated precisions in optimal ways.In this work we present a novel methodology to speed up multilevel Monte Carlo (MLMC) simulations on reconfigurable architectures. The idea is to aggressively lower the precisions for different parts of the algorithm without loosing any accuracy at the end. For this, we have developed a novel heuristic for selecting an appropriate precision at each stage of the simulation that can be executed with low costs at runtime. Further, we introduce a cost model for reconfigurable architectures and minimize the cost of our algorithm without changing the overall error.We consider the showcase of pricing Asian options in the Heston model. For this setup we improve one of the most advanced simulation methods by a factor of 3-9x on the same platform.