SRAMminner

SRAMminner is a conceptual framework and set of techniques aimed at optimizing the use of static random-access memory (SRAM) in embedded and system-on-a-chip environments. It combines hardware support with software interfaces to improve memory locality, reduce latency, and lower energy consumption in systems where SRAM is a critical resource.

The core idea of SRAMminner is to partition SRAM into banks and tiles that can be managed more predictably. It includes a hardware-assisted scratchpad memory manager that can assign data to specific banks based on access patterns and a software API that allows developers and compilers to annotate data lifetimes and meantAccess patterns. A memory controller enhancement coordinates bank interleaving, prefetching, and bank conflict avoidance to deliver more deterministic, low-latency accesses.

From a software perspective, SRAMminner provides a memory allocation API and a set of compiler hints to guide data placement. Developers annotate critical data structures, such as real-time buffers or neural inference layers, to reside in SRAM tiles with known access characteristics. The runtime system enforces these placements, performing lightweight relocations when lifetimes end or when data reuse is detected. Toolchains may include static analyzers and simulators to estimate cache-like behavior without traditional caches.

Applications and benefits include real-time embedded systems, automotive controllers, and edge devices where SRAM is the dominant constraint. By improving data locality and reducing cache misses in SRAM-based designs, SRAMminner can decrease latency, increase throughput, and extend the usable SRAM footprint for application code.

Status and adoption are theoretical in nature, with research prototypes demonstrating potential gains in controlled experiments. SRAMminner remains a topic of interest for memory hierarchy design and compiler-runtime co-optimization discussions.