We realize an AI framework-agnostic interposer to test memory allocations on the NVIDIA Grace Hopper (GH200) Superchip, ranging from below the High Bandwidth Memory (HBM) limit, i.e., < 96 GB, to the HBM limit of 96 GB and beyond. When the HBM limit is exceeded, the coherent CPU+GPU memory of the GH200 can turn what wo...
Mohamed Abdelnaby, Wu-Chun Feng· Workshop Proceedings of the...· 0 citations
Many real-world applications such as bioinformatics, network analysis, and recommendation systems require computing intersections of vertex neighborhood sets in graph datasets. However, variability in graph sparsity patterns makes it challenging to design a single GPU optimization strategy for such workloads that perfo...
Atharva Gondhalekar, Wu-Chun Feng· Proceedings of the Internati...· 0 citations
Architectural diversity has turned accelerator performance portability into a compiler/runtime problem: portable source code is useful only if the surrounding ecosystem can also coordinate devices, backends, and data movement. This paper evaluates three SYCL ecosystems—Intel oneAPI DPC++, AdaptiveCpp, and UniSYCL—acros...
Nabayan Chaudhury, Norihisa Fujita, Beau Johnston et al.· International Conference on...· 0 citations
Overall, when evaluating both Chapel and MPI+X implementations of partitioned Jaccard similarity on up to 16 A100-80GB GPUs across four nodes, Chapel achieves comparable performance to MPI+X while also delivering significantly better programmer productivity and agility.
Paul Sathre, Wu-Chun Feng· Proceedings of the Internati...· 0 citations
A fine-grained GPU parallelization approach that adapts to workload characteristics by assigning set intersection computations within a graph to the most suitable parallelization strategies, and predicts the optimal parallelization approach between this fine-grained and other state-of-the-art GPU kernels with 88% accur...
Atharva Gondhalekar, Wu-Chun Feng· Proceedings of the Internati...· 0 citations
Overall, when evaluating both Chapel and MPI+X implementations of partitioned Jaccard similarity on up to 16 A100-80GB GPUs across four nodes, Chapel achieves comparable performance to MPI+X while also delivering significantly better programmer productivity and agility.
Paul Sathre, Wu-Chun Feng· Proceedings of the Internati...· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
