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Many natural processes exhibit exponential decay and, consequently, computational scientists make extensive use of e<sup>-χx</sup> in computer simulation experiments. While it is common to implement transcendental functions (sine, cosine, exponentiation, etc.) in hardware using the well-known CORDIC algorithm, many contemporary FPGA implementations… (More)
Financial exchanges provide real time data feeds containing trade, order and status information to brokers, traders and other market makers. ITCH is one such market data feed that is disseminated by the NASDAQ exchange. The work presented in this paper describes an FPGA based ITCH feed handler and processing system. The handler, built on the Stone Ridge… (More)
Many natural processes exhibit exponential decay and, consequently, computational scientists make extensive use of e −x in computer simulations. Many transcenden-tal functions (sine, cosine, tangent, exponentiation, etc) are readily and efficiently implemented in hardware using the well known CORDIC algorithm. However, many current FPGA implementations are… (More)
Sparse Matrix Vector-Multiplication is an important operation for many iterative solvers. However, peak performance is limited by the fact that the commonly used algorithm alternates between compute-bound and memory-bound steps. This paper proposes a novel data structure and an FPGA-based hardware core that eliminates the limitations imposed by memory.
The computer simulation of three-body potentials using the Stillinger-Weber method has been extensively used in the study of three-body molecular forces between partially rigid molecules such as silicon. The Stillinger-Weber method of computing three-body interactions is generally computationally intense. This paper presents a FPGA-based framework that is… (More)
OBJECTIVE Seeking a full-time teaching/research position in the field of high performance computing, or embedded systems, or application acceleration using FPGAs from August 2014. My PhD dissertation focuses on building FPGA accelerators for living computational science applications. Living computational science applications are those applications whose… (More)
A neural network is an information processing system that is widely used in various computer vision applications. This paper discusses an low-latency FPGA-based neural network implementation that does direct computation of the sigmoid activation function.