Peter Skoda

Learn More
In recent decades there has been an exponential growth in quantity of collected data. Various data mining procedures have been developed to extract information from such large amounts of data. Handling ever increasing amount of data generates increasing demand for computing power. There are several ways of dealing with this demand, such as multiprocessor(More)
In an Artificial Neural Network (ANN) a large number of highly interconnected simple nonlinear processing units work in parallel to solve a specific problem. Parallelism, modularity and dynamic adaptation are three characteristics typically associated with ANNs. Field Programmable Gate Array (FPGA) based reconfigurable computing architectures are well(More)
– Frequency table computation is a common procedure used in variety of machine learning algorithms. In this paper we present a parallelized kernel for computing frequency tables. The kernel is targeted for dataflow architecture implemented on field programmable gate array (FPGA). Its performance was evaluated against a parallelized software implementation(More)
This paper describes the measurement method and experimental technique with advanced instrumentation setup for analysing the metastability behavior and performance measurement of flip-flops used in programmable logic devices. In order to demonstrate this testing approach, the results for metastable characteristics parameters of one FPGA digital circuit(More)
  • 1