Cloud Data Centers have become the key infrastructure for providing services. Instance
migration across different computing nodes in edge and cloud computing is essential to …

The abstraction of a shared memory space over separate CPU and GPU memory domains
has eased the burden of portability for many HPC codebases. However, users pay for the …

Bandwidth non-uniformity in multi-chip GPUs poses a major design challenge for its last-
level cache (LLC) architecture. Whereas a memory-side LLC caches data from the local …

Multi-GPU systems have emerged as a desirable platform to deliver high computing
capabilities and large memory capacity to accommodate large dataset sizes. However …

Recent work has shown that building GPUs with hundreds of SMs in a single monolithic chip
will not be practical due to slowing growth in transistor density, low chip yields, and …

In recent years, the ever-growing application complexity and input dataset sizes have driven
the popularity of multi-GPU systems as a desirable computing platform for many application …

Suboptimal management of memory and bandwidth is one of the primary causes of low
performance on systems comprising multiple GPUs. Existing memory management solutions …

With GPUs becoming ubiquitous in HPC systems, NVIDIA's Unified Virtual Memory (UVM) is
being adopted as a measure to simplify porting of complex codes to GPU platforms by …

This paper presents an address translation scheme in GPUs named SnakeByte that can
dynamically manage variable-sized pages and maximize TLB reach by recursively merging …

GPUs, due to their massively-parallel computing architectures, provide high performance for
data-parallel applications. However, existing GPU simulators are too slow to enable …