November 13–18, 2023

Booth #2048 

The International Conference for High Performance Computing, Networking, Storage, and Analysis

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Programming Novel AI Accelerators for Scientific Computing

Session time: Sunday, Nov 12, 2023
Time: 8:30am – 12:00am MST
Location: Rm 203


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


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


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)


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


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.


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


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.