As AI models grow larger and more complex, delivering real-time insights requires fast and frictionless access to massive datasets. At the same time, controlling AI token costs has become critical. However, the volume of KVCache for inference is skyrocketing, and enterprises are hitting the “GPU memory wall”—limited GPU VRAM prevents models from fully utilizing their compute power. GPU memory bottlenecks, underutilized GPUs, and high latency slow down workflows, limiting the speed and accuracy of AI applications across industries.
TuringData Cache Fabric is a revolutionary solution designed to address these critical challenges with ultra-fast performance, low latency, and seamless scalability. By building a three-tier hierarchical caching architecture—spanning GPU and host memory, local NVMe SSDs, and the TuringData file system—and optimizing KVCache flow, TuringData Cache Fabric ensures fast data access and maximum GPU inference concurrency. This dramatically lowers latency and reduces AI inference costs, enabling organizations to deliver real-time, accurate insights at scale.
Easily integrates with vLLM, SGLang, TensorRT-LLM, and TGI via standardized APIs, requiring no code changes and abstracting away framework and version differences to simplify integration.
TuringData Cache Fabric fully leverages all available storage resources—including GPU VRAM, CPU DRAM, and local NVMe SSDs—without additional hardware. Optionally, it can connect to PB-scale TuringData Platform shared high-speed storage, keeping investment requirements low.
By optimizing KVCache access and storage strategies, TuringData Cache Fabric significantly reduces time-to-first-token (TTFT) and increases token throughput, delivering a faster, smoother inference experience for end users.
Offloads KVCache to high-performance storage to prevent GPU memory swapping and performance fluctuations. This enables higher batch sizes and concurrency, maximizing GPU efficiency, and reducing both overall and per-token costs.
High-performance, low-latency storage with a distributed architecture enables seamless data access across cloud, hybrid, and on-premises environments, with smooth integration into modern orchestration tools.
TuringData Cache Fabric:
Enabling Fast and Cost-Efficient AI Inferencing
TuringData’s AI inference solution seamlessly integrates with major LLM inference frameworks, requires no extra hardware, extends GPU memory, and boosts GPU utilization by letting LLMs reuse precomputed key-value pairs on the fly—dramatically accelerating token generation and reducing costs.Download the Solution Brief