MemoryEfficient

Memoryefficient refers to software, algorithms, data structures, or hardware designs that minimize memory consumption while preserving acceptable performance. The term highlights a small and predictable memory footprint, reduced peak allocations, and efficient use of cache and RAM. Memory-efficient solutions often achieve their goals through in-place computations, streaming or one-pass processing, lazy evaluation, compact data representations, and selective caching or compression.

In practice, pursuing memory efficiency involves trade-offs. Reducing memory use can increase CPU time, add complexity, or complicate concurrent access. The appropriate balance depends on constraints such as available RAM, energy consumption, latency requirements, and the size of data sets. Common domains include embedded systems, mobile devices, and large-scale data processing where memory is a critical cost factor.

Techniques commonly associated with memory efficiency include in-place data structures (for example, bit-packed arrays or compact hash maps), streaming algorithms that process data as it arrives, windowed or chunked processing to bound memory, lazy evaluation to defer work until necessary, and on-the-fly compression with selective decompression. Memory pooling and careful allocator choices can also reduce fragmentation and overhead.

Measuring memory efficiency involves metrics such as memory footprint, peak memory usage, and resident set size. Profiling tools help identify allocations, garbage-collection pressure, and cache misses. See also memory footprint, streaming algorithm, in-place algorithm, lazy evaluation, and data compression.