2025-09 monthly summary: Focused on delivering a robust HiCache backend overhaul for bytedance-iaas/sglang, with memory management improvements, eviction logic simplifications, and API cleanup to improve reliability, data organization, and developer experience. Implemented bug fixes to memory release paths and simplified API surface, driving stability and performance.

In August 2025, the sgLang project delivered substantial HiCache enhancements, an API expansion for Mooncake, and enhanced benchmarking/docs, delivering higher reliability, throughput, and developer efficiency for caching workloads used across distributed services.

July 2025 performance summary for bytedance-iaas/sglang. This period focused on delivering kernel-level optimizations for the KV cache, advancing HiCache storage and memory management, and enhancing benchmarking tooling to improve measurement reliability and reproducibility. The work enhances scalability, reduces cache IO latency, and strengthens memory efficiency, aligning with business goals of faster KV lookups, lower memory pressure, and more reliable performance telemetry.

June 2025 monthly summary for bytedance-iaas/sglang. Delivered two high-impact items that strengthen cache reliability and performance. (1) CUDA-Accelerated KV Cache I/O: introduced CUDA kernels and Python bindings for efficient KV cache I/O, enabling per-layer and cross-layer data transfers with direct memory transfers and kernel-based optimizations; added tests. (2) HiCache Synchronization Stability Improvements: upstreamed fixes to improve HiCache synchronization and data handling, including LayerDoneCounter overlap mode management and benchmark input processing for stability and correctness. These changes improve runtime throughput, reduce latency in KV cache operations, and increase stability for benchmarks and production workloads. Technical focus included CUDA kernel development, Python bindings, per-layer/cross-layer data transfers, and up-to-date test coverage. Business value centers on faster, more reliable KV cache I/O and a more stable caching layer, enabling scalable workloads and smoother upstream contributions.

May 2025 monthly summary for bytedance-iaas/sglang. Focused on stability and memory-management improvements in the prefill pipeline to handle large-page workloads safely. Delivered targeted fixes to prevent Out-Of-Memory (OOM) during prefill when using large page sizes by correcting input token calculations against page boundaries and by ensuring at least one page is available before starting chunked prefill. These changes reduce memory pressure, prevent crashes, and improve robustness across varying page sizes and workloads.

April 2025 (2025-04) performance and reliability month for bytedance-iaas/sglang. Delivered feature upgrades to GPU runtime with Dependency upgrades (Cutlass and DeepGEMM) to ensure stability and compatibility, implemented hierarchical cache enhancements with larger page sizes, configurable hicache sizing and policies, and improved eviction scheduling; fixed HiRadix eviction issues and write-backs; resolved a memory leak in retract_decode affecting batch scheduling. These changes improved runtime stability, memory usage, and overall throughput under high-load scenarios, delivering measurable business value in resource efficiency and operational reliability.

March 2025 monthly summary for bytedance-iaas/sglang focused on memory management, caching, and reliability improvements that elevate throughput, stability, and observability. Delivered architectural overhauls to KV caching, enhanced multi-layer caching strategies, and a critical fix to metrics accounting. These changes improve memory efficiency, reduce risk of out-of-memory events, and provide more predictable token accounting under retraction scenarios.

February 2025 monthly summary focusing on key accomplishments and technical impact for the fzyzcjy/sglang repo. Central achievement: build and deployment of SGLang hierarchical KV cache to accelerate multi-turn conversations, with write-through and load-back strategies, alongside a new benchmarking suite and memory pooling optimizations to boost throughput and reduce latency.

January 2025 monthly work summary for repository fzyzcjy/sglang focused on delivering a scalable, memory-efficient KV cache platform to support large-model workloads.