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nodes
Azure HBv4
Azure HBv5
Azure ND A100 v4
Azure ND GB200 v6
Azure ND H100 v5
Azure ND MI200 v4
Azure ND MI300X v5
BullSequana XH3406-3
BullSequana XH3515
Cray EX154n
Cray EX235a
Cray EX235n
Cray EX254n
Cray EX255a
Cray EX425
papers
A democratic vision for artificial intelligence must prevail over an authoritarian one.
Azure Accelerated Networking: SmartNICs in the Public Cloud
Big Tech Is Rushing to Find Clean Power to Fuel AI’s Insatiable Appetite
Carbon-Removal Firms Have One Very Big Backer. That’s a Problem
Datacenters to emit 3x more carbon dioxide because of genAI
FASST RFI
Machines of Loving Grace
Nuclear finance will rely on consumers’ stomach for risk
Pre-Training GPT-4.5
Recommendations on Powering Artificial Intelligence and Data Center Infrastructure
Revisiting Reliability in Large-Scale Machine Learning Research Clusters
The Intelligence Age
The National Security Case for Public AI - Vanderbilt Policy Accelerator
processors
AMD MI250X
AMD MI300A
AMD MI300X
AMD MI325X
AMD MI355X
Ascend 910
Custom A100 GPUs
Custom H100 GPUs
Google TPUv4
Intel Ponte Vecchio
Microsoft Maia 100
NVIDIA A100
NVIDIA B200
NVIDIA B300
NVIDIA GH200
NVIDIA Grace
NVIDIA H100
NVIDIA H200
NVIDIA R200
NVIDIA R300
Trainium2
systems
ABCI 3.0 (AIST)
Alps (CSCS)
Aurora (ALCF)
Colossus (xAI)
Eagle (Microsoft)
El Capitan (LLNL)
Fir (SFU)
Frontier (OLCF)
Fugaku (R-CCS)
FugakuNEXT (R-CCS)
Horizon (TACC)
Isambard-AI (Bristol)
JUPITER (JSC)
KISTI-6 (KISTI)
Leonardo (CINECA)
Meta's H100 clusters
New Sunway (Wuxi)
Niagra
Perlmutter (NERSC)
Project Ceiba (AWS)
Project Rainier (AWS)
Red Storm (Sandia)
Sunway TaihuLight (Wuxi)
Tianhe-3
Vista (TACC)
tags
usa
NSF
U.S. Department of Energy
Artificial intelligence
canada
Europe
Papers
Reliability
seedling
storage
Azure SmartNICs
Co-ops
discrete event simulation
Dragonfly topology
elbencho
Government's role in AI
InfiniBand
IOR
LLM training
LLM training at scale
LLM training datasets
mdtest
Microsoft supercomputers
MTBF, FIT, and AFR
NFS
Nuclear energy
Scaling laws
Sustainability in HPC
thermodynamics
Ultra Ethernet
3FS
AI datacenters
AMD CDNA
availability
Azure infrastructure
blobfuse
Broadcom Tomahawk 5
BXI
cables and connectors
Canadian sovereign AI
capex
checkpointing
China
CIFAR
Coarse-Grained Reconfigurable Array
component reliability
Cray EX
Crusoe
DAOS
Darshan
DeepSeek-R1
Denvr Dataworks
differences between AI and HPC
digital garden
Digital Research Alliance of Canada
distillation
Dragonfly+ topology
DRAM architecture
Duane Arnold
ECC schemes
European sovereign AI
excursions
FASST
fio
foundation models for science
Frontier models
GekkoFS
GPU terminology decoder ring
GPUaaS
GSP and SMC
GTC25
High-Performance Linpack
Hypertec
IR7000
Job Mean Time To Interrupt
job reliability
jobs
LCCF
LLM inferencing
LPDDR5 Reliability
LRA
Lustre
manufacturing level
memory bandwidth
Mercury
Meta Llama-3.1
Meta Movie Gen
Minipack2
mixture of experts
Model FLOPs Utilization
Mt. Diablo
Multi-plane topologies
multicluster training
NAIRR
natural gas
Network flow
Networking for LLM training
Neuromorphic computing
New Frontiers
Niagara
NVIDIA Vera
NVLink
Obsidian
OPT-175B
Optical circuit switch
Palisades nuclear plant
PCIe Gen6
peer review
pod
Podman
POSIX
power infrastructure
Productivity tools
QScale
quantum
Read-it-later apps
Reasoning models
reinforcement learning
Salishan
SC Conference
Signal modulation
silent data corruption
Slingshot
Slurm
Small Language Models
Social media platforms
sovereign AI
Spectrum-X Photonics
Stargate Project
Storage for LLM training
Structured sparsity
Superintelligence
Synthetic data
System architect
Tensor cores and Matrix cores
test-time compute
Three Mile Island
transformer
VAST
wisdom
working at Microsoft
Home
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PINN
PINN
Jun 24, 2025
seedling
artificial-intelligence
I think PINNs are “physics-informed neural networks.”
Graph View
Backlinks
FugakuNEXT (R-CCS)