// learn together

Technical Meetups

Every meetup is part of a structured curriculum. Sessions are technical, progressive, and engineering focused—not general networking events.

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// every session

What to Expect

🖼️
Architecture DiagramsReal system designs, not marketing slides
💻
Live DemonstrationsWorking systems, live on stage
⚙️
Hands-on ExamplesCode, configs, and real deployments
🏭
Production DiscussionsWar stories from real-world systems
Open Technical Q&AHonest peer-to-peer discussion
📚
Progressive CurriculumEach session builds on the last

// topics we go deep on

Engineering at the Deepest Level

We don't do introductory overviews. Every IMLG session targets engineers who want to understand how things work at the systems level.

GPU Architecture

Streaming multiprocessors, Tensor Cores, HBM, NVLink and NVSwitch topologies

CUDA & Libraries

CUDA programming model, Triton, and the NVIDIA ecosystem — cuBLAS, NCCL, NIXL, cuDNN

Interconnects

Intra-node and inter-node communication: PCIe, GPUDirect, RDMA, DPU

Distributed Training

Data, model, pipeline, and tensor parallelism; FSDP; Megatron-LM; torch.compile

MLOps

Experiment tracking, feature stores, vector and graph databases, serving pipelines

LLMOps

KV cache management, speculative decoding, PEFT, RLHF strategies, inference optimization

GPU Observability

DCGM, Nsight, OpenTelemetry, Prometheus, ClickHouse, Grafana

LLM Observability

OpenLLMetry, Langfuse, Phoenix, TTFT and ITL SLOs

Platform Engineering

Linux administration and platform engineering for GPU infrastructure

Deployment

Edge (Jetson, NPU), on-prem GPU servers, and cloud GPU instances

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