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HomeCalculatorsMemory Calculator

About Memory Calculator

Memory Calculator preview - Calculators tool

Calculate memory usage for data structures (arrays, linked lists, trees, hash tables). Part of the DevTools Surf developer suite. Browse more tools in the Calculators collection.

Use Cases

  • Calculate the memory footprint of a data structure before choosing between array and linked list implementations.
  • Estimate cache efficiency by computing how many elements fit in L1/L2/L3 cache for a specific data type.
  • Compare memory usage of different hash table load factors to find the size-performance trade-off.
  • Estimate the RAM needed to load a large dataset before running an in-memory sort or join.

Tips

  • Account for pointer size (8 bytes on 64-bit systems) in linked list and tree calculations — each node's pointers add significant overhead compared to array storage.
  • Use the cache line size (64 bytes on x86) to understand false sharing — two variables in adjacent memory accessed by different CPU cores can cause cache coherence traffic.
  • Compare struct-of-arrays vs. array-of-structs memory layouts to understand the cache performance tradeoff for data-intensive algorithms.

Fun Facts

  • A boolean value in Java takes 1 byte of memory despite needing only 1 bit — JVM memory alignment requirements inflate single-bit values to full bytes.
  • Memory alignment requirements mean that a C struct {char a; int b;} typically uses 8 bytes, not 5 — the compiler pads 3 bytes after 'a' to align 'b' on a 4-byte boundary.
  • A 1-million-element array of 64-bit doubles requires 8MB of memory. The same data in a naive linked list (pointer + value) takes 16MB — linked lists have 2x memory overhead for primitive types.

FAQ

Does it account for memory alignment and padding?
Yes — struct layout calculations apply C/C++ alignment rules (each field aligned to its size, struct padded to largest member's alignment). Java and Python overhead models are separate.
Does it support complex data structures?
Arrays, linked lists, doubly-linked lists, binary trees, B-trees, hash tables (open addressing and chaining), and heaps are all modeled with configurable element count and type.
Can it estimate Java object overhead?
Java object header (12-16 bytes) and reference size (4 bytes compressed OOP, 8 bytes 64-bit) are included in Java mode. Boxed primitive overhead (Integer vs. int) is also shown.

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