Lincoln: Real-Time 50~100B LLM Inference on Consumer Devices with LPDDR-Interfaced, Compute-Enabled Flash Memory

With the widespread use of large language models (LLMs), and with the privacy and cost concerns on cloud-based services, vendors are now pushing LLM inference to consumer devices. However, current attempts only enable real-time inference of low-quality small-sized LLMs. Large-sized LLMs have to load most of their weights from Flash storage for every execution iteration, which dominates the execution time of both the prefill and the generation phase. This performance bottleneck is attributed to both the low internal Flash memory bandwidth and the low transmission bandwidth between Flash and the Neural Processing Unit (NPU). To tackle these two challenges, we present Lincoln, a device-architecture co-design solution with LPDDR-interfaced, Compute-Enabled Flash Memory. On the device level, we boost the Flash internal bandwidth by improving upon existing array shrinking methods, to enable lower read latency and more parallel Flash planes within each Flash die. We specifically leverage 3D hybrid bonding, which is already adopted in consumer Flash products, to maintain high area efficiency and low density loss. On the architecture level, to leverage such increased internal bandwidth for resolving the transmission bottleneck, we propose two solutions for the two distinct phases of LLMs. For the compute-intensive prefill phase, we let Flash devices use the existing high-speed LPDDR interface (originally for DRAM), which offers much higher transmission bandwidth to the NPU than the conventional Flash interface, while maintaining good cost and area efficiency. For the memory-intensive generation phase, we rely on hybrid-bonding-based near-Flash computing to fully utilize the internal Flash bandwidth, and further equip with speculative decoding to eventually reach the real-time latency goal. Our evaluation shows that Lincoln enables real-time inference, with up to $13.23 \times$ and $254.1 \times$ speedups for LLM prefill and generation phases over conventional SSD-based systems.