1# Introduction 2 3Several tables in the opentype format are formed internally by a graph of subtables. Parent node's 4reference their children through the use of positive offsets, which are typically 16 bits wide. 5Since offsets are always positive this forms a directed acyclic graph. For storage in the font file 6the graph must be given a topological ordering and then the subtables packed in serial according to 7that ordering. Since 16 bit offsets have a maximum value of 65,535 if the distance between a parent 8subtable and a child is more then 65,535 bytes then it's not possible for the offset to encode that 9edge. 10 11For many fonts with complex layout rules (such as Arabic) it's not unusual for the tables containing 12layout rules ([GSUB/GPOS](https://docs.microsoft.com/en-us/typography/opentype/spec/gsub)) to be 13larger than 65kb. As a result these types of fonts are susceptible to offset overflows when 14serializing to the binary font format. 15 16Offset overflows can happen for a variety of reasons and require different strategies to resolve: 17* Simple overflows can often be resolved with a different topological ordering. 18* If a subtable has many parents this can result in the link from furthest parent(s) 19 being at risk for overflows. In these cases it's possible to duplicate the shared subtable which 20 allows it to be placed closer to it's parent. 21* If subtables exist which are themselves larger than 65kb it's not possible for any offsets to point 22 past them. In these cases the subtable can usually be split into two smaller subtables to allow 23 for more flexibility in the ordering. 24* In GSUB/GPOS overflows from Lookup subtables can be resolved by changing the Lookup to an extension 25 lookup which uses a 32 bit offset instead of 16 bit offset. 26 27In general there isn't a simple solution to produce an optimal topological ordering for a given graph. 28Finding an ordering which doesn't overflow is a NP hard problem. Existing solutions use heuristics 29which attempt a combination of the above strategies to attempt to find a non-overflowing configuration. 30 31The harfbuzz subsetting library 32[includes a repacking algorithm](https://github.com/harfbuzz/harfbuzz/blob/main/src/hb-repacker.hh) 33which is used to resolve offset overflows that are present in the subsetted tables it produces. This 34document provides a deep dive into how the harfbuzz repacking algorithm works. 35 36Other implementations exist, such as in 37[fontTools](https://github.com/fonttools/fonttools/blob/7af43123d49c188fcef4e540fa94796b3b44e858/Lib/fontTools/ttLib/tables/otBase.py#L72), however these are not covered in this document. 38 39# Foundations 40 41There's four key pieces to the harfbuzz approach: 42 43* Subtable Graph: a table's internal structure is abstracted out into a lightweight graph 44 representation where each subtable is a node and each offset forms an edge. The nodes only need 45 to know how many bytes the corresponding subtable occupies. This lightweight representation can 46 be easily modified to test new ordering's and strategies as the repacking algorithm iterates. 47 48* [Topological sorting algorithm](https://en.wikipedia.org/wiki/Topological_sorting): an algorithm 49 which given a graph gives a linear sorting of the nodes such that all offsets will be positive. 50 51* Overflow check: given a graph and a topological sorting it checks if there will be any overflows 52 in any of the offsets. If there are overflows it returns a list of (parent, child) tuples that 53 will overflow. Since the graph has information on the size of each subtable it's straightforward 54 to calculate the final position of each subtable and then check if any offsets to it will 55 overflow. 56 57* Content Aware Preprocessing: if the overflow resolver is aware of the format of the underlying 58 tables (eg. GSUB, GPOS) then in some cases preprocessing can be done to increase the chance of 59 successfully packing the graph. For example for GSUB and GPOS we can preprocess the graph and 60 promote lookups to extension lookups (upgrades a 16 bit offset to 32 bits) or split large lookup 61 subtables into two or more pieces. 62 63* Offset resolution strategies: given a particular occurrence of an overflow these strategies 64 modify the graph to attempt to resolve the overflow. 65 66# High Level Algorithm 67 68``` 69def repack(graph): 70 graph.topological_sort() 71 72 if (graph.will_overflow()) 73 preprocess(graph) 74 assign_spaces(graph) 75 graph.topological_sort() 76 77 while (overflows = graph.will_overflow()): 78 for overflow in overflows: 79 apply_offset_resolution_strategy (overflow, graph) 80 graph.topological_sort() 81``` 82 83The actual code for this processing loop can be found in the function hb_resolve_overflows () of 84[hb-repacker.hh](https://github.com/harfbuzz/harfbuzz/blob/main/src/hb-repacker.hh). 85 86# Topological Sorting Algorithms 87 88The harfbuzz repacker uses two different algorithms for topological sorting: 89* [Kahn's Algorithm](https://en.wikipedia.org/wiki/Topological_sorting#Kahn's_algorithm) 90* Sorting by shortest distance 91 92Kahn's algorithm is approximately twice as fast as the shortest distance sort so that is attempted 93first (only on the first topological sort). If it fails to eliminate overflows then shortest distance 94sort will be used for all subsequent topological sorting operations. 95 96## Shortest Distance Sort 97 98This algorithm orders the nodes based on total distance to each node. Nodes with a shorter distance 99are ordered first. 100 101The "weight" of an edge is the sum of the size of the sub-table being pointed to plus 2^16 for a 16 bit 102offset and 2^32 for a 32 bit offset. 103 104The distance of a node is the sum of all weights along the shortest path from the root to that node 105plus a priority modifier (used to change where nodes are placed by moving increasing or 106decreasing the effective distance). Ties between nodes with the same distance are broken based 107on the order of the offset in the sub table bytes. 108 109The shortest distance to each node is determined using 110[Djikstra's algorithm](https://en.wikipedia.org/wiki/Dijkstra%27s_algorithm). Then the topological 111ordering is produce by applying a modified version of Kahn's algorithm that uses a priority queue 112based on the shortest distance to each node. 113 114## Optimizing the Sorting 115 116The topological sorting operation is the core of the repacker and is run on each iteration so it needs 117to be as fast as possible. There's a few things that are done to speed up subsequent sorting 118operations: 119 120* The number of incoming edges to each node is cached. This is required by the Kahn's algorithm 121 portion of both sorts. Where possible when the graph is modified we manually update the cached 122 edge counts of affected nodes. 123 124* The distance to each node is cached. Where possible when the graph is modified we manually update 125 the cached distances of any affected nodes. 126 127Caching these values allows the repacker to avoid recalculating them for the full graph on each 128iteration. 129 130The other important factor to speed is a fast priority queue which is a core datastructure to 131the topological sorting algorithm. Currently a basic heap based queue is used. Heap based queue's 132don't support fast priority decreases, but that can be worked around by just adding redundant entries 133to the priority queue and filtering the older ones out when poppping off entries. This is based 134on the recommendations in 135[a study of the practical performance of priority queues in Dijkstra's algorithm](https://www3.cs.stonybrook.edu/~rezaul/papers/TR-07-54.pdf) 136 137## Special Handling of 32 bit Offsets 138 139If a graph contains multiple 32 bit offsets then the shortest distance sorting will be likely be 140suboptimal. For example consider the case where a graph contains two 32 bit offsets that each point 141to a subgraph which are not connected to each other. The shortest distance sort will interleave the 142subtables of the two subgraphs, potentially resulting in overflows. Since each of these subgraphs are 143independent of each other, and 32 bit offsets can point extremely long distances a better strategy is 144to pack the first subgraph in it's entirety and then have the second subgraph packed after with the 32 145bit offset pointing over the first subgraph. For example given the graph: 146 147 148``` 149a--- b -- d -- f 150 \ 151 \_ c -- e -- g 152``` 153 154Where the links from a to b and a to c are 32 bit offsets, the shortest distance sort would be: 155 156``` 157a, b, c, d, e, f, g 158 159``` 160 161If nodes d and e have a combined size greater than 65kb then the offset from d to f will overflow. 162A better ordering is: 163 164``` 165a, b, d, f, c, e, g 166``` 167 168The ability for 32 bit offsets to point long distances is utilized to jump over the subgraph of 169b which gives the remaining 16 bit offsets a better chance of not overflowing. 170 171The above is an ideal situation where the subgraphs are disconnected from each other, in practice 172this is often not this case. So this idea can be generalized as follows: 173 174If there is a subgraph that is only reachable from one or more 32 bit offsets, then: 175* That subgraph can be treated as an independent unit and all nodes of the subgraph packed in isolation 176 from the rest of the graph. 177* In a table that occupies less than 4gb of space (in practice all fonts), that packed independent 178 subgraph can be placed anywhere after the parent nodes without overflowing the 32 bit offsets from 179 the parent nodes. 180 181The sorting algorithm incorporates this via a "space" modifier that can be applied to nodes in the 182graph. By default all nodes are treated as being in space zero. If a node is given a non-zero space, n, 183then the computed distance to the node will be modified by adding `n * 2^32`. This will cause that 184node and it's descendants to be packed between all nodes in space n-1 and space n+1. Resulting in a 185topological sort like: 186 187``` 188| space 0 subtables | space 1 subtables | .... | space n subtables | 189``` 190 191The assign_spaces() step in the high level algorithm is responsible for identifying independent 192subgraphs and assigning unique spaces to each one. More information on the space assignment can be 193found in the next section. 194 195# Graph Preprocessing 196 197For certain table types we can preprocess and modify the graph structure to reduce the occurences 198of overflows. Currently the repacker implements preprocessing only for GPOS and GSUB tables. 199 200## GSUB/GPOS Table Splitting 201 202The GSUB/GPOS preprocessor scans each lookup subtable and determines if the subtable's children are 203so large that no overflow resolution is possible (for example a single subtable that exceeds 65kb 204cannot be pointed over). When such cases are detected table splitting is invoked: 205 206* The subtable is first analyzed to determine the smallest number of split points that will allow 207 for successful offset overflow resolution. 208 209* Then the subtable in the graph representation is modified to actually perform the split at the 210 previously computed split points. At a high level splits are done by inserting new subtables 211 which contain a subset of the data of the original subtable and then shrinking the original subtable. 212 213Table splitting must be aware of the underlying format of each subtable type and thus needs custom 214code for each subtable type. Currently subtable splitting is only supported for GPOS subtable types. 215 216## GSUB/GPOS Extension Lookup Promotion 217 218In GSUB/GPOS tables lookups can be regular lookups which use 16 bit offsets to the children subtables 219or extension lookups which use 32 bit offsets to the children subtables. If the sub graph of all 220regular lookups is too large then it can be difficult to find an overflow free configuration. This 221can be remedied by promoting one or more regular lookups to extension lookups. 222 223During preprocessing the graph is scanned to determine the size of the subgraph of regular lookups. 224If the graph is found to be too big then the analysis finds a set of lookups to promote to reduce 225the subgraph size. Lastly the graph is modified to convert those lookups to extension lookups. 226 227# Offset Resolution Strategies 228 229## Space Assignment 230 231The goal of space assignment is to find connected subgraphs that are only reachable via 32 bit offsets 232and then assign each such subgraph to a unique non-zero space. The algorithm is roughly: 233 2341. Collect the set, `S`, of nodes that are children of 32 bit offsets. 235 2362. Do a directed traversal from each node in `S` and collect all encountered nodes into set `T`. 237 Mark all nodes in the graph that are not in `T` as being in space 0. 238 2393. Set `next_space = 1`. 240 2414. While set `S` is not empty: 242 243 a. Pick a node `n` in set `S` then perform an undirected graph traversal and find the set `Q` of 244 nodes that are reachable from `n`. 245 246 b. During traversal if a node, `m`, has a edge to a node in space 0 then `m` must be duplicated 247 to disconnect it from space 0. 248 249 d. Remove all nodes in `Q` from `S` and assign all nodes in `Q` to `next_space`. 250 251 252 c. Increment `next_space` by one. 253 254 255## Manual Iterative Resolutions 256 257For each overflow in each iteration the algorithm will attempt to apply offset overflow resolution 258strategies to eliminate the overflow. The type of strategy applied is dependent on the characteristics 259of the overflowing link: 260 261* If the overflowing offset is inside a space other than space 0 and the subgraph space has more 262 than one 32 bit offset pointing into the subgraph then subdivide the space by moving subgraph 263 from one of the 32 bit offsets into a new space via the duplication of shared nodes. 264 265* If the overflowing offset is pointing to a subtable with more than one incoming edge: duplicate 266 the node so that the overflowing offset is pointing at it's own copy of that node. 267 268* Otherwise, attempt to move the child subtable closer to it's parent. This is accomplished by 269 raising the priority of all children of the parent. Next time the topological sort is run the 270 children will be ordered closer to the parent. 271 272# Test Cases 273 274The harfbuzz repacker has tests defined using generic graphs: https://github.com/harfbuzz/harfbuzz/blob/main/src/test-repacker.cc 275 276# Future Improvements 277 278Currently for GPOS tables the repacker implementation is sufficient to handle both subsetting and the 279general case of font compilation repacking. However for GSUB the repacker is only sufficient for 280subsetting related overflows. To enable general case repacking of GSUB, support for splitting of 281GSUB subtables will need to be added. Other table types such as COLRv1 shouldn't require table 282splitting due to the wide use of 24 bit offsets throughout the table. 283 284Beyond subtable splitting there are a couple of "nice to have" improvements, but these are not required 285to support the general case: 286 287* Extension demotion: currently extension promotion is supported but in some cases if the non-extension 288 subgraph is underfilled then packed size can be reduced by demoting extension lookups back to regular 289 lookups. 290 291* Currently only children nodes are moved to resolve offsets. However, in many cases moving a parent 292 node closer to it's children will have less impact on the size of other offsets. Thus the algorithm 293 should use a heuristic (based on parent and child subtable sizes) to decide if the children's 294 priority should be increased or the parent's priority decreased. 295