xAI Grok Architecture: Training Data and Compute Stack
xAI Grok architecture explained: how xAI built Grok from training data to JAX/Rust compute infrastructure and GPU clusters.
Tag: JAX
Speculative Decoding Infrastructure: Squeezing Latency without Hardware Upgrades
The bottleneck for LLMs is memory bandwidth, not compute. Discover how to use speculative decoding on GCP to achieve 3x speedups by using small "draft" models to accelerate massive "oracle" models.
JAX Pallas Kernels: Write GPU Kernels for Max Performance
JAX Pallas kernels: NVIDIA GPU programming API for high-performance compute. Write optimized kernels for matrix multiplication and memory access.
Single-Batch Inference: Speculative Decoding on an A100
See how speculative decoding performs for single-batch requests on an NVIDIA A100. We analyze acceptance rates, latency, and the mechanics of the draft model gamble.
MoE Routing Collapse: When Your Specialists Stop Specializing
A model is only as smart as its router. We explore the physics of expert zones, the tax of token dropping, and how to keep your load balancer honest.
JAX XLA: Why Your GPU is Idle 40% of the Time
Recompilation is the silent killer of training throughput. If you see 'Jit' in your profiler, you are losing money. We dive into XLA internals.