Heterogeneous system architectures are evolving towards tighter integration among
devices, with emerging features such as shared virtual memory, memory coherence, and …

Segmented sort, as a generalization of classical sort, orders a batch of independent
segments in a whole array. Along with the wider adoption of manycore processors for HPC …

Chiplets are transforming computer system designs, allowing system designers to combine
heterogeneous computing resources at unprecedented scales. Breaking larger, mono-lithic …

From edge to exascale, computer architectures are becoming more heterogeneous and
complex. The systems typically have fat nodes, with multicore CPUs and multiple hardware …

GPUs lack fundamental support for data-dependent parallelism and synchronization. While
CUDA Dynamic Parallelism signals progress in this direction, many limitations and …

Scaling neural network models has delivered dramatic quality gains across ML problems.
However, this scaling has increased the reliance on efficient distributed training techniques …

As modern GPU workloads grow in size and complexity, there is an ever-increasing demand
for GPU computational power. Emerging workloads contain hundreds or thousands of GPU …

Pipeline is an important programming pattern, while GPU, designed mostly for data-level
parallel executions, lacks an efficient mechanism to support pipeline programming and …

With the skyrocketing advances of process technology, the increased need to process huge
amount of data, and the pivotal need for power efficiency, the usage of Graphics Processing …

As GPUs become larger and provide an increasing number of parallel execution units, a
single kernel is no longer sufficient to utilize all available resources. As a result, GPU …