Gathering place for AI researchers to find curated information about using ACCESS resources for AI applications and research.
NCSA Delta GPU (Delta GPU)
The Delta GPU resource comprises 4 different node configurations intended to support accelerated computation across a broad range of domains such as soft-matter physics, molecular dynamics, replica-exchange molecular dynamics, machine learning, deep learning, natural language processing, textual analysis, visualization, ray tracing, and accelerated analysis of very large in-memory datasets.
Purdue Anvil GPU
Purdue's Anvil GPU cluster is comprised of 16 GPU nodes (each with 128 cores, 256 GB of memory, and four NVIDIA A100 Tensor Core GPUs) providing 1.5 PF of single-precision performance to support machine learning and artificial intelligence applications. All CPU cores are AMD's "Milan" architecture running at 2.0 GHz, and all nodes are interconnected using a 100 Gbps HDR Infiniband fabric. Scratch storage consists of a 10+ PB parallel filesystem with over 3 PB of flash drives. Storage for active projects is provided by Purdue's Research Data Depot, and data archival is available via Purdue's Fortress tape archive. The operating system is CentOS 8, and the batch scheduling system is Slurm.
Indiana Jetstream2 GPU
Jetstream2 is a user-friendly cloud environment designed to give researchers and students access to computing and data analysis resources on demand as well as for gateway and other infrastructure projects.
PSC Bridges-2 GPU-AI (Bridges-2 GPU Artificial Intelligence)
Bridges-2 Accelerated GPU (GPU) nodes are optimized for scalable artificial intelligence (AI; deep learning). Bridges-2 GPU nodes each contain 8 NVIDIA Tesla V100-32GB SXM2 GPUs, providing 40,960 CUDA cores and 5,120 tensor cores. In addition, each node holds 2 Intel Xeon Gold 6248 CPUs; 512GB of DDR4-2933 RAM; and 7.68TB NVMe SSD. They are connected to Bridges-2's other compute nodes and its Ocean parallel filesystem and archive by two HDR-200 InfiniBand links, providing 400Gbps of bandwidth to enhance scalability of deep learning training.
SDSC Expanse GPU
Expanse GPU will be a Dell integrated cluster, NVIDIA V100 GPUs with NVLINK, interconnected with Mellanox HDR InfiniBand in a hybrid fat-tree topology.
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