Papers by ahmed sanaullah
BMC Bioinformatics, 2018
Background: Real-time analysis of patient data during medical procedures can provide vital diagno... more Background: Real-time analysis of patient data during medical procedures can provide vital diagnostic feedback that significantly improves chances of success. With sensors becoming increasingly fast, frameworks such as Deep Neural Networks are required to perform calculations within the strict timing constraints for real-time operation. However, traditional computing platforms responsible for running these algorithms incur a large overhead due to communication protocols, memory accesses, and static (often generic) architectures. In this work, we implement a low-latency Multi-Layer Perceptron (MLP) processor using Field Programmable Gate Arrays (FPGAs). Unlike CPUs and Graphics Processing Units (GPUs), our FPGA-based design can directly interface sensors, storage devices, display devices and even actuators, thus reducing the delays of data movement between ports and compute pipelines. Moreover, the compute pipelines themselves are tailored specifically to the application, improving resource utilization and reducing idle cycles. We demonstrate the effectiveness of our approach using mass-spectrometry data sets for real-time cancer detection. Results: We demonstrate that correct parameter sizing, based on the application, can reduce latency by 20% on average. Furthermore, we show that in an application with tightly coupled data-path and latency constraints, having a large amount of computing resources can actually reduce performance. Using mass-spectrometry benchmarks, we show that our proposed FPGA design outperforms both CPU and GPU implementations, with an average speedup of 144x and 21x, respectively. Conclusion: In our work, we demonstrate the importance of application-specific optimizations in order to minimize latency and maximize resource utilization for MLP inference. By directly interfacing and processing sensor data with ultra-low latency, FPGAs can perform real-time analysis during procedures and provide diagnostic feedback that can be critical to achieving higher percentages of successful patient outcomes.
— In this paper we present a general software quality model, providing the possibility to describ... more — In this paper we present a general software quality model, providing the possibility to describe different concepts related to quality. We show that our quality model is able to integrate the various concepts found in quality standards and different quality models. Furthermore, we provide different quality views related to software quality, enabling consistency and continuity of quality-related information. The most influential factor for the developers of software is the customer perception. We connect the developer with the customer to derive a common interpretation for quality. This paper introduces a model for software quality by connecting and integrating the different views of software quality. In addition, it connects the customer view with the developer view of software quality and it treats software as a product.
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Papers by ahmed sanaullah