Zero-knowledge proof is a cryptographic primitive that allows for the validation of statements without disclosing any sensitive information, foundational in applications like verifiable outsourcing and digital currency. However, the extensive proof ...

Multi-chip Graphics Processing Unit (GPU) systems are critical to scale performance beyond a single GPU chip for a wide variety of important emerging applications. A key challenge for multi-chip GPUs, though, is how to overcome the bandwidth gap between ...

High-performance computing (HPC) workloads such as scientific simulations and deep learning (DL) running across multi-GPU systems are memory and data-intensive, relying on the main memory to complement its limited onboard high-bandwidth memory (HBM). To ...

Influence maximization is an advanced graph-theoretic operation that aims to identify a set of k most influential nodes in a network. The problem is of immense interest in many network applications (e.g., information spread in a social network, or ...

The rapidly growing popularity and scale of data-parallel workloads demand a corresponding increase in raw computational power of Graphics Processing Units (GPUs). As single-GPU platforms struggle to satisfy these performance demands, multi-GPU ...

Graphics Processing Unit (GPU) vendors have been scaling single-GPU architectures to satisfy the ever-increasing user demands for faster graphics processing. However, as it gets extremely difficult to further scale single-GPU architectures, the vendors ...

The communication overhead is one of the main challenges in the exascale era, where millions of compute cores are expected to collaborate on solving complex jobs. However, many algorithms will not scale since they require complex global communication ...

Currently the set of scientific applications suitable for running on GPUs has increased due to the computational power of GPUs and the availability of programming languages that make more approachable writing scientific applications for GPUs. However, ...

In this paper, we present a multi-level programming model for recent GPU-based high performance computing systems. Involving cooperative stream threads and symmetric multiprocessing threads our model gives a computational framework that scales through ...