https://www.youngju.dev/blog 천천히 올바르게. AI Researcher & DevOps Engineer Youngju's tech blog. GPU/CUDA, LLM, MLOps, Kubernetes AI workloads, distributed training, and data engineering. ko fjvbn2003@gmail.com (Youngju Kim) fjvbn2003@gmail.com (Youngju Kim) Tue, 16 Jun 2026 00:00:00 GMT https://www.youngju.dev/blog/gpu-cuda/2026-06-16-inference-hardware-quantization-sparsity-dataflow.en https://www.youngju.dev/blog/gpu-cuda/2026-06-16-inference-hardware-quantization-sparsity-dataflow.en We break down the cost structure of inference through the memory-wall lens, then connect quantization (INT8/FP8/FP4), structured sparsity (2:4), dataflow architectures, operator fusion, batching and KV caching into one picture of hardware-software co-design. Reflects the 2026 reality of Blackwell FP4 and the Vera Rubin trajectory, with practical guidance for shipping fast inference. Tue, 16 Jun 2026 00:00:00 GMT fjvbn2003@gmail.com (Youngju Kim) inferencequantizationsparsitydataflowgpuhardwareoptimization https://www.youngju.dev/blog/gpu-cuda/2026-06-16-inference-hardware-quantization-sparsity-dataflow.ja https://www.youngju.dev/blog/gpu-cuda/2026-06-16-inference-hardware-quantization-sparsity-dataflow.ja 推論コストの構造をメモリウォールの観点から解きほぐし、量子化(INT8/FP8/FP4)、構造化スパース性(2:4)、dataflow アーキテクチャ、演算子融合、バッチングと KV キャッシュまでをハードウェアとソフトウェアの協調設計として一枚の絵にまとめます。2026 年の Blackwell FP4 と Vera Rubin の流れを反映し、実務での適用ポイントを示します。 Tue, 16 Jun 2026 00:00:00 GMT fjvbn2003@gmail.com (Youngju Kim) inferencequantizationsparsitydataflowgpuhardwareoptimization https://www.youngju.dev/blog/gpu-cuda/2026-06-16-inference-hardware-quantization-sparsity-dataflow https://www.youngju.dev/blog/gpu-cuda/2026-06-16-inference-hardware-quantization-sparsity-dataflow 추론 비용의 구조를 메모리 월 관점에서 풀어내고, 양자화(INT8/FP8/FP4)와 구조적 희소성(2:4), dataflow 아키텍처, 연산자 융합, 배칭과 KV 캐시까지 하드웨어-소프트웨어 공동설계의 큰 그림을 정리합니다. 2026년 Blackwell FP4와 Vera Rubin 흐름을 반영해 실무 적용 포인트를 짚습니다. Tue, 16 Jun 2026 00:00:00 GMT fjvbn2003@gmail.com (Youngju Kim) inferencequantizationsparsitydataflowgpuhardwareoptimization