This paper presents a novel nearest neighbor search algorithm achieving TPU (Google
Tensor Processing Unit) peak performance, outperforming state-of-the-art GPU algorithms …

GPUs offer massive parallelism and high-bandwidth memory access, making them an
attractive option for accelerating data analytics in database systems. However, while modern …

Pairwise sequence alignment is one of the most computationally intensive kernels in
genomic data analysis, accounting for more than 90% of the runtime for key bioinformatics …

With reconfigurable fabrics delivering increasing performance over the years, Field-
Programmable Gate Arrays (FPGAs) are becoming an appealing solution for next …

In this paper, we present PPT-GPU, a scalable performance prediction toolkit for GPUs. PPT-
GPU achieves scalability through a hybrid high-level modeling approach where some …

HPC has undergone a significant transition toward heterogeneous architectures. This
transition has introduced several issues in code migration to support multiple frameworks for …

Over the past few decades, the gap between rapidly increasing computational power and
almost stagnating memory bandwidth has steadily worsened. Recently, 3D die-stacking in …

Finding a novel drug is a very long and complex procedure. Using computer simulations, it is
possible to accelerate the preliminary phases by performing a virtual screening that filters a …

The intrinsic complexity of modern computing systems requires structured methods for
analyzing and optimizing application performance. In this context, the Roofline model …

This paper presents a practical methodology for collecting performance data necessary to
conduct hierarchical Roofline analysis on NVIDIA GPUs. It discusses the extension of the …