event
SC23
November 13–18, 2023
Booth #2048
The International Conference for High Performance Computing, Networking, Storage, and Analysis
Tutorial
Programming Novel AI Accelerators for Scientific Computing
Session time: Sunday, Nov 12, 2023
Time: 8:30am – 12:00am MST
Location: Rm 203
session
14th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Heterogeneous Systems
Session time: Tuesday, Nov 13, 2023
Time: 11:30am – 11:50am MST
Location: 710
Session Title: Massively Distributed Finite-Volume Flux Computation
Partner: TotalEnergies and Lawrence Livermore National Laboratory
Session
ACM Student Research Competition Posters Display
Session time: Tuesday, Nov 14, 2023
Time: 10:00am – 5:00pm MST
Location: 710
Session Title: Near-Optimal Reduce on the Cerebras Wafer-Scale Engine
Partner: ETH Zürich
award
ACM Gordon Bell Finalists Presentations
Session time: Wednesday, Nov 15, 2023
Time: 4:30pm – 5:00pm MST
Location: 501-502
Session Title: Scaling the “Memory Wall” for Multi-Dimensional Seismic Processing with Algebraic Compression on Cerebras CS-2 Systems
Partner: King Abdullah University of Science and Technology (KAUST)
session
Birds of a Feather
Session time: Wednesday, Nov 15, 2023
Time: 5:15pm – 6:45pm MST
Location: 503-504
Session Title: Advances in FPGA Programming and Technology for HPC
blog
Context is Everything: Why Maximum Sequence Length Matters
GPU-Impossible™ sequence lengths on Cerebras systems may enable breakthroughs in Natural Language Understanding, drug discovery and genomics.
Blog
Cerebras Sets Record for Largest AI Models Ever Trained on Single Device
Our customers can easily train and reconfigure GPT-3 and GPT-J language models with up to 20 billion parameters on a single CS-2 system
Blog
TotalEnergies and Cerebras Create Massively Scalable Stencil Algorithm
TotalEnergies used the Cerebras CS-2 system to turn a problem long accepted to be memory-bound into compute-bound. On a benchmark case inspired by a seismic kernel used to image the Earth, the CS-2 delivered more than 200x performance compared to a NVIDIA® A100 GPU.