Folder: papers

- What I have learned
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
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

Glenn's Digital Garden

Explorer

Folder: papers

Revisiting Reliability in Large-Scale Machine Learning Research Clusters

Pre-Training GPT-4.5

Machines of Loving Grace

Nuclear finance will rely on consumers’ stomach for risk

The National Security Case for Public AI - Vanderbilt Policy Accelerator

The Intelligence Age

Recommendations on Powering Artificial Intelligence and Data Center Infrastructure

Carbon-Removal Firms Have One Very Big Backer. That’s a Problem

Datacenters to emit 3x more carbon dioxide because of genAI

Big Tech Is Rushing to Find Clean Power to Fuel AI’s Insatiable Appetite

A democratic vision for artificial intelligence must prevail over an authoritarian one.

FASST RFI

Azure Accelerated Networking: SmartNICs in the Public Cloud