Concept

Miss rate — where it appears

The share of memory accesses a modelled cache cannot satisfy, which is the second count beside comparisons and ranks algorithms differently. It is the second count beside comparisons and it ranks algorithms differently, which is the whole reason this collection models a cache at all.

Named by 9 essays across 4 fields — each of them below, with the objects they name alongside it.

0%25%50%75%100%645124,09665,536cache holds 512array size n (elements)miss ratefully associative · 64 lines × 8 elements · LRU20,000 random accesses per point

The cliff where the data stops fitting

Below the cache's capacity, almost every access hits. A factor of eight above it, almost every access misses. The transition is not gradual and it is not a property of any algorithm — it is a property of how much data there is, and an algorithm's complexity class says nothing about which side of it a program is working on.

machine · Machine
comparisonsswapsInsertion sort63,071 / 0Selection sort130,816 / 504Bubble sort129,688 / 62,563Merge sort3,964 / 0Heapsort7,653 / 4,170Quicksort5,049 / 2,380n = 512, random inputcounted in the same run

The count somebody chose

Six quantities can now be measured for every sort. Ranking the ten algorithms by each of them and comparing the orders, comparisons and peak space disagree about 91% of all pairs, and memory traffic and modelled misses disagree about 7%. There is no ranking of sorting algorithms; there are six, and choosing between them is a statement about the data rather than about the algorithms.

counting · Count
10³10³10⁴Vmodelled missesadjacency listCSR array96% miss27% miss64 lines × 8 elements, fully associative, LRU3.6× between two layouts of one graph

A list and a block of memory

The same traversal, over the same graph, examining the same edges in the same order, laid out two ways. Twelve thousand two hundred and eighty-eight edge slots either way; 11,812 modelled cache misses against 3,258. This is the site's largest gap between two counts of one run, and it exists because one of the layouts is a pointer chase and the other is a sweep.

graphs · Graph
01234567801234567891724303539424410182531364043111926323741122027333813212834142229152316one unit = one subproblem given a valueeach number is a storage offset, of 45 slots

A triangle stored in a square

An interval table has a cell for every range of keys and nothing below its diagonal, and it can be stored as a square array, as packed rows, or as packed diagonals — the last matching the order it is filled in. On sixty-four keys, with every read replayed through a small cache, the square misses 39.7% of its reads, packed rows 38.8%, and packed diagonals 78.4%. Storing a table in the order it is written is storing it in the order it is not read.

tables · Table
cache misses per split point consideredsquare array, by length1.1063,128,465 missestwo copies, by rows0.212598,455 missessquare array, split scans0.095268,386 missesfully associative · 32 lines × 8 elements · LRU256 keys, 32,896 cells

The split scan cut into blocks

Every way of filling an interval table one cell at a time stops at about one cache miss per split point considered once the table outgrows the cache — 1.01 at 128 keys, whether the cells go by length, by rows, or in a recursive tiling. Cut each cell's scan into blocks instead, and apply a block of split points to a block of cells whose inputs are all in hand, recursively at every scale, and the same 357,760 split points cost 0.094 misses each. The fill is told nothing about the cache, blocks of one and of four do equally well, and it needs no extra memory, where storing the table twice gets to 0.151 by doubling it.

tables · Table
rounds, if every ready cell ran at oncerow by row65,793column by column65,793anti-diagonal by anti-diagonal513reads that miss the cacherow by row6.3%column by column28.2%anti-diagonal by anti-diagonal31.1%fully associative · 32 lines × 8 elements · LRU263,169 reads and writes per order

The order with the best depth

An edit-distance table can be filled row by row, column by column, or one anti-diagonal at a time, and the anti-diagonal order is the one that needs the fewest rounds — 513 against 65,793 on two strings of 256 characters, because every cell on an anti-diagonal is independent of the others. Stored the usual way, row by row, it also misses the cache on 31.1% of its reads, where row order misses 6.3%. The order that is best for parallel work is worst for the memory it runs on.

machine · Machine
linear probingchainedcuckoo, two tables0240.10.20.30.40.50.60.70.80.9load factorentries read per lookup0120.10.20.30.40.50.60.70.80.9load factorcache misses per lookup8,192 slots, 64 cache lines of 8a probe is an entry read; a miss is a line fetched

Two probes are two misses

Cuckoo hashing's lookup reads at most two slots, and at a load of 0.45 it reads 1.27 on average where linear probing reads 1.39. Replayed through a cache, it misses 1.18 times a lookup where linear probing misses 0.98. The table that wins the count the analysis uses loses the count the machine charges, because two slots in unrelated places are two cache lines, and a run of adjacent slots is usually one.

machine · Machine
linear probingcuckoo, two tablescuckoo, buckets of 8024680.30.450.60.750.850.95load factorentries read per lookup00.511.50.30.450.60.750.850.95load factorcache misses per lookup8,192 slots, 64 cache lines of 8a probe is an entry read; a miss is a line fetched

The bucket that fits a line

Make each of a cuckoo table's two candidates a bucket of eight slots laid out on one cache line, and no lookup ever touches more than two lines, the table builds past a load of 0.95, and at that load it misses 1.21 times a lookup where linear probing misses 1.79. The prediction that it would lose to linear probing at low loads was wrong — it misses less at every load measured, 0.94 against 0.96 at 0.3 — because a key it holds almost never lives in its second bucket. The guarantee belongs to the alignment, not the bucket; eight slots on lines of four put a lookup on four lines.

machine · Machine
rounds, if every ready cell ran at oncerow order, stored by rows65,793anti-diagonal order, stored by rows513anti-diagonal order, stored by diagonals513reads that miss the cacherow order, stored by rows6.3%anti-diagonal order, stored by rows31.1%anti-diagonal order, stored by diagonals8.7%fully associative · 32 lines × 8 elements · LRU263,169 reads and writes per order

The table stored the way it is filled

Store an edit-distance table by anti-diagonals instead of by rows, and the anti-diagonal fill keeps its 513 rounds while its cache misses fall from 31.1% of reads to 8.7%. It does not fall to row order's 6.3%, and the gap is not noise — on caches of four and eight lines the two rates are 9.4% and 6.3%, exactly three to two, because a cell reads from two earlier diagonals and only one earlier row. The same layout turns row order into the order that strides, at 28.3%. How a table is stored and the order it is filled in are one decision, and its price is the number of earlier fronts the recurrence reads.

machine · Machine

Named alongside it

The objects these essays reach for when they reach for this one.

CacheLocalityMemory layoutAccess patternWorking setEvaluation orderTrade offChained hashingCompulsory missCuckoo hashingDepthDynamic programming

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