Current FPGA programming tools require extensive hardware-specific manual code tuning
to achieve performance, which is intractable for most software application teams. We present …

We introduce the Bayesian Compiler Optimization framework (BaCO), a general purpose
autotuner for modern compilers targeting CPUs, GPUs, and FPGAs. BaCO provides the …

Sketching algorithms are a powerful tool for single-pass data summarization. Their
numerous applications include approximate query processing, machine learning, and large …

In this paper, we show that true 3D placement approaches, enhanced with reinforcement
learning, can offer further PPA improvements over pseudo-3D approaches. To accomplish …

Signature and behavior-based anti-virus systems (AVS) are traditionally used to detect
Malware. However, these AVS fail to catch metamorphic and polymorphic Malware-which …

A large amount of resources is spent writing, porting, and optimizing scientific and industrial
High Performance Computing applications, which makes autotuning techniques …

Neural processing applications are widely used in many fields like vision, speech
recognition and language processing to realize artificial intelligence, but they are very …

Martin Kiefer Page 1 Accelerating Approximate Data Analysis with Parallel Processors 2.2.2023
Martin Kiefer PhD Defense Page 2 Approximate Data Analysis Trading accuracy for faster …

Recently, FPGAs have become widely available in heterogeneous systems and public
clouds, taking them beyond the traditional audience of hardware designers and making …

High-Level Synthesis (HLS) is the process of generating digital circuits from high-level
algorithmic descriptions. One of the major steps in this design approach is scheduling, which …