Accelerating Data Analytics Through Emerging Software-Hardware Mechanisms

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The objectives of this research are to investigate algorithms, design, and architectures for enabling an efficient real-time event data analytics platform to support multi-query processing over high-volume and high-frequency event streams. To achieve these objectives, we plan to leverage modern hardware mechanisms, such as Field Programmable Gate Arrays (FPGAs) and Application Processing Units (APUs) in our design. We strive to achieve line-rate multi-query processing by exploiting unprecedented degrees of parallelism and potential for pipelining, only available through custom-built, application-specific and low-level logic design. Furthermore, we intend to compare against the use of emerging Graphical Processing Units (GPUs) in our design, evaluating above all performance, but also development effort.