Performance3 articles

Performance

Articles

Continuous LLM Performance Profiling in Production: Roofline Models, Model FLOPs Utilization, Model Bandwidth Utilization, and Hardware Bottleneck Diagnostics
Evaluating the runtime performance of large language model serving infrastructures requires looking beyond raw GPU metrics. Standard operating system utilities such as nvidia-smi report high GPU utilization percentages whenever compute cores or memory controllers are active, masking critical inefficiencies in memory access, communication, and kernel scheduling. A serving node running single-stream autoregressive decoding can report 100% GPU utilization while operating at less than 2% of the hard
August 24, 20261 min
Dynamic Context Assembly and Token Budget Allocation in Production: Priority Packing, Prefix Cache Alignment, and Degradation Fallbacks
In production large language model systems, prompt construction is frequently treated as simple string concatenation. Engineers assemble system instructions, tool schemas, retrieved document snippets, memory state, and multi-turn conversational history using template strings. In low-throughput prototypes, this approach functions adequately. In high-throughput production systems and multi-agent workflows, naive assembly introduces critical failure modes: abrupt context window overflows triggering
August 21, 20261 min
Quantized KV Caches in Production: FP8 vs. INT8 vs. INT4 Architecture, Kernel Backends, and Serving Economics
In modern large language model serving, memory capacity and memory bandwidth are the two primary bottlenecks governing inference economics. While static model weights occupy a fixed footprint in GPU High Bandwidth Memory (HBM), the Key-Value (KV) cache grows dynamically with batch size and sequence length. In workloads with 32,000 to 128,000 token context windows, the KV cache quickly overtakes weight memory, consuming up to 70% of total VRAM and capping concurrency. During autoregressive gener
August 19, 20261 min

Performance

Continuous LLM Performance Profiling in Production: Roofline Models, Model FLOPs Utilization, Model Bandwidth Utilization, and Hardware Bottleneck Diagnostics

Dynamic Context Assembly and Token Budget Allocation in Production: Priority Packing, Prefix Cache Alignment, and Degradation Fallbacks

Quantized KV Caches in Production: FP8 vs. INT8 vs. INT4 Architecture, Kernel Backends, and Serving Economics