Inputs
Use bytes for sizes. Defaults are safe estimates and can be adjusted.
Example Data Table
Use these sample assumptions as a starting point, then refine using your actual layout and allocator behavior.
| Scenario | Base bytes | Pointers | Padding | Elems/alloc | Allocs | Alignment | Overhead | Slack % |
|---|---|---|---|---|---|---|---|---|
| Telemetry samples ring buffer | 24 | 0 | 0 | 4096 | 1 | 16 | 32 | 5 |
| Hash table node pool | 32 | 2 | 8 | 2048 | 4 | 16 | 16 | 10 |
| Image tiles cache blocks | 64 | 1 | 0 | 512 | 32 | 64 | 64 | 12 |
Formula Used
How to Use This Calculator
- Set Base element size using your struct or record layout.
- Add Pointers per element and select the correct pointer size.
- Enter Elements per allocation and Number of allocations.
- Adjust Alignment, Overhead, and Header bytes if known.
- Add Slack to reflect allocator gaps or fragmentation.
- Press Calculate, then export CSV or PDF.
Engineering Notes
Capacity planning starts with element anatomy
Memory budgeting improves when you decompose each stored element into payload bytes, pointer fields, and explicit padding. A 32-byte record with two 8-byte pointers already becomes 48 bytes before allocator effects. Multiply that effective element size by elements per allocation to estimate the raw payload per block, then compare it with your platform limits, such as SRAM, heap pools, or container quotas.
Alignment changes real usage more than expected
Allocators and hardware often round requests up to alignment boundaries for speed and correctness. When payloads are not multiples of the alignment, every allocation gains slack. For example, a 65,540-byte payload aligned to 64 bytes rounds up to 65,600 bytes, adding 60 bytes per block. Over thousands of blocks, those small increments become measurable megabytes and can move a system from safe headroom to fragmentation risk.
Overhead and headers accumulate at scale
Per-allocation overhead includes allocator metadata, free-list links, guard bytes, or bookkeeping required by the runtime. Application headers add more: container fields, counters, timestamps, or checksums. If you allocate 10,000 blocks and each carries 16 bytes of overhead plus 24 bytes of header, you spend 400,000 bytes before storing a single record. Treat these fixed costs like taxes that scale with allocation count, not element count.
Slack factors model fragmentation and growth
Fragmentation is rarely uniform, but a conservative slack percentage helps represent real-world gaps caused by churn, uneven lifetimes, and size-class rounding. A 10% slack factor on a 200 MiB base footprint reserves an extra 20 MiB to survive bursts and long-running behavior. Use higher slack when allocations are frequently created and destroyed, and lower slack for static pools with predictable lifetimes and stable sizes.
Compression helps payload, not management costs
When payload data is compressible, a compression ratio reduces the aligned payload while leaving overhead and headers unchanged. This means the benefit depends on how payload-dominant your footprint is. If overhead is significant, compression delivers smaller gains than expected. Validate your ratio using representative datasets and consider CPU cost, latency, and worst-case incompressible blocks. A measured ratio plus explicit slack yields defensible capacity figures for reviews under pressure and variability.
FAQs
1) What should I enter as base element size?
Use the bytes of the stored record itself, excluding referenced data. Measure with your compiler’s sizeof output, or a language memory profiler, then adjust for manual padding.
2) Why does alignment increase my footprint?
Allocators round each allocation up to an alignment boundary. The extra rounded space is not available for payload, so it becomes slack that accumulates across many allocations.
3) Does compression reduce overhead and headers too?
No. The calculator applies compression only to the aligned payload. Metadata, allocator overhead, and container headers usually remain fixed, so total savings depend on payload share.
4) How do I choose a fragmentation percentage?
Start with 5–15% for dynamic heaps with churn. Use 0–5% for static pools. Increase it if you see rising RSS, failed allocations, or long uptimes with varied sizes.
5) What is allocation overhead in practice?
It represents bookkeeping added by allocators: size fields, free-list links, fences, and alignment padding outside your payload. Different runtimes and build modes can change it.
6) How can I validate these estimates?
Compare the predicted totals with runtime measurements: heap snapshots, malloc stats, RSS, or embedded memory maps. Validate on representative workloads and capture best, typical, and worst cases.