295 lines
15 KiB
Markdown
295 lines
15 KiB
Markdown
# Introduction
|
|
|
|
Several tables in the opentype format are formed internally by a graph of subtables. Parent node's
|
|
reference their children through the use of positive offsets, which are typically 16 bits wide.
|
|
Since offsets are always positive this forms a directed acyclic graph. For storage in the font file
|
|
the graph must be given a topological ordering and then the subtables packed in serial according to
|
|
that ordering. Since 16 bit offsets have a maximum value of 65,535 if the distance between a parent
|
|
subtable and a child is more then 65,535 bytes then it's not possible for the offset to encode that
|
|
edge.
|
|
|
|
For many fonts with complex layout rules (such as Arabic) it's not unusual for the tables containing
|
|
layout rules ([GSUB/GPOS](https://docs.microsoft.com/en-us/typography/opentype/spec/gsub)) to be
|
|
larger than 65kb. As a result these types of fonts are susceptible to offset overflows when
|
|
serializing to the binary font format.
|
|
|
|
Offset overflows can happen for a variety of reasons and require different strategies to resolve:
|
|
* Simple overflows can often be resolved with a different topological ordering.
|
|
* If a subtable has many parents this can result in the link from furthest parent(s)
|
|
being at risk for overflows. In these cases it's possible to duplicate the shared subtable which
|
|
allows it to be placed closer to it's parent.
|
|
* If subtables exist which are themselves larger than 65kb it's not possible for any offsets to point
|
|
past them. In these cases the subtable can usually be split into two smaller subtables to allow
|
|
for more flexibility in the ordering.
|
|
* In GSUB/GPOS overflows from Lookup subtables can be resolved by changing the Lookup to an extension
|
|
lookup which uses a 32 bit offset instead of 16 bit offset.
|
|
|
|
In general there isn't a simple solution to produce an optimal topological ordering for a given graph.
|
|
Finding an ordering which doesn't overflow is a NP hard problem. Existing solutions use heuristics
|
|
which attempt a combination of the above strategies to attempt to find a non-overflowing configuration.
|
|
|
|
The harfbuzz subsetting library
|
|
[includes a repacking algorithm](https://github.com/harfbuzz/harfbuzz/blob/main/src/hb-repacker.hh)
|
|
which is used to resolve offset overflows that are present in the subsetted tables it produces. This
|
|
document provides a deep dive into how the harfbuzz repacking algorithm works.
|
|
|
|
Other implementations exist, such as in
|
|
[fontTools](https://github.com/fonttools/fonttools/blob/7af43123d49c188fcef4e540fa94796b3b44e858/Lib/fontTools/ttLib/tables/otBase.py#L72), however these are not covered in this document.
|
|
|
|
# Foundations
|
|
|
|
There's four key pieces to the harfbuzz approach:
|
|
|
|
* Subtable Graph: a table's internal structure is abstracted out into a lightweight graph
|
|
representation where each subtable is a node and each offset forms an edge. The nodes only need
|
|
to know how many bytes the corresponding subtable occupies. This lightweight representation can
|
|
be easily modified to test new ordering's and strategies as the repacking algorithm iterates.
|
|
|
|
* [Topological sorting algorithm](https://en.wikipedia.org/wiki/Topological_sorting): an algorithm
|
|
which given a graph gives a linear sorting of the nodes such that all offsets will be positive.
|
|
|
|
* Overflow check: given a graph and a topological sorting it checks if there will be any overflows
|
|
in any of the offsets. If there are overflows it returns a list of (parent, child) tuples that
|
|
will overflow. Since the graph has information on the size of each subtable it's straightforward
|
|
to calculate the final position of each subtable and then check if any offsets to it will
|
|
overflow.
|
|
|
|
* Content Aware Preprocessing: if the overflow resolver is aware of the format of the underlying
|
|
tables (eg. GSUB, GPOS) then in some cases preprocessing can be done to increase the chance of
|
|
successfully packing the graph. For example for GSUB and GPOS we can preprocess the graph and
|
|
promote lookups to extension lookups (upgrades a 16 bit offset to 32 bits) or split large lookup
|
|
subtables into two or more pieces.
|
|
|
|
* Offset resolution strategies: given a particular occurrence of an overflow these strategies
|
|
modify the graph to attempt to resolve the overflow.
|
|
|
|
# High Level Algorithm
|
|
|
|
```
|
|
def repack(graph):
|
|
graph.topological_sort()
|
|
|
|
if (graph.will_overflow())
|
|
preprocess(graph)
|
|
assign_spaces(graph)
|
|
graph.topological_sort()
|
|
|
|
while (overflows = graph.will_overflow()):
|
|
for overflow in overflows:
|
|
apply_offset_resolution_strategy (overflow, graph)
|
|
graph.topological_sort()
|
|
```
|
|
|
|
The actual code for this processing loop can be found in the function hb_resolve_overflows () of
|
|
[hb-repacker.hh](https://github.com/harfbuzz/harfbuzz/blob/main/src/hb-repacker.hh).
|
|
|
|
# Topological Sorting Algorithms
|
|
|
|
The harfbuzz repacker uses two different algorithms for topological sorting:
|
|
* [Kahn's Algorithm](https://en.wikipedia.org/wiki/Topological_sorting#Kahn's_algorithm)
|
|
* Sorting by shortest distance
|
|
|
|
Kahn's algorithm is approximately twice as fast as the shortest distance sort so that is attempted
|
|
first (only on the first topological sort). If it fails to eliminate overflows then shortest distance
|
|
sort will be used for all subsequent topological sorting operations.
|
|
|
|
## Shortest Distance Sort
|
|
|
|
This algorithm orders the nodes based on total distance to each node. Nodes with a shorter distance
|
|
are ordered first.
|
|
|
|
The "weight" of an edge is the sum of the size of the sub-table being pointed to plus 2^16 for a 16 bit
|
|
offset and 2^32 for a 32 bit offset.
|
|
|
|
The distance of a node is the sum of all weights along the shortest path from the root to that node
|
|
plus a priority modifier (used to change where nodes are placed by moving increasing or
|
|
decreasing the effective distance). Ties between nodes with the same distance are broken based
|
|
on the order of the offset in the sub table bytes.
|
|
|
|
The shortest distance to each node is determined using
|
|
[Djikstra's algorithm](https://en.wikipedia.org/wiki/Dijkstra%27s_algorithm). Then the topological
|
|
ordering is produce by applying a modified version of Kahn's algorithm that uses a priority queue
|
|
based on the shortest distance to each node.
|
|
|
|
## Optimizing the Sorting
|
|
|
|
The topological sorting operation is the core of the repacker and is run on each iteration so it needs
|
|
to be as fast as possible. There's a few things that are done to speed up subsequent sorting
|
|
operations:
|
|
|
|
* The number of incoming edges to each node is cached. This is required by the Kahn's algorithm
|
|
portion of both sorts. Where possible when the graph is modified we manually update the cached
|
|
edge counts of affected nodes.
|
|
|
|
* The distance to each node is cached. Where possible when the graph is modified we manually update
|
|
the cached distances of any affected nodes.
|
|
|
|
Caching these values allows the repacker to avoid recalculating them for the full graph on each
|
|
iteration.
|
|
|
|
The other important factor to speed is a fast priority queue which is a core datastructure to
|
|
the topological sorting algorithm. Currently a basic heap based queue is used. Heap based queue's
|
|
don't support fast priority decreases, but that can be worked around by just adding redundant entries
|
|
to the priority queue and filtering the older ones out when poppping off entries. This is based
|
|
on the recommendations in
|
|
[a study of the practical performance of priority queues in Dijkstra's algorithm](https://www3.cs.stonybrook.edu/~rezaul/papers/TR-07-54.pdf)
|
|
|
|
## Special Handling of 32 bit Offsets
|
|
|
|
If a graph contains multiple 32 bit offsets then the shortest distance sorting will be likely be
|
|
suboptimal. For example consider the case where a graph contains two 32 bit offsets that each point
|
|
to a subgraph which are not connected to each other. The shortest distance sort will interleave the
|
|
subtables of the two subgraphs, potentially resulting in overflows. Since each of these subgraphs are
|
|
independent of each other, and 32 bit offsets can point extremely long distances a better strategy is
|
|
to pack the first subgraph in it's entirety and then have the second subgraph packed after with the 32
|
|
bit offset pointing over the first subgraph. For example given the graph:
|
|
|
|
|
|
```
|
|
a--- b -- d -- f
|
|
\
|
|
\_ c -- e -- g
|
|
```
|
|
|
|
Where the links from a to b and a to c are 32 bit offsets, the shortest distance sort would be:
|
|
|
|
```
|
|
a, b, c, d, e, f, g
|
|
|
|
```
|
|
|
|
If nodes d and e have a combined size greater than 65kb then the offset from d to f will overflow.
|
|
A better ordering is:
|
|
|
|
```
|
|
a, b, d, f, c, e, g
|
|
```
|
|
|
|
The ability for 32 bit offsets to point long distances is utilized to jump over the subgraph of
|
|
b which gives the remaining 16 bit offsets a better chance of not overflowing.
|
|
|
|
The above is an ideal situation where the subgraphs are disconnected from each other, in practice
|
|
this is often not this case. So this idea can be generalized as follows:
|
|
|
|
If there is a subgraph that is only reachable from one or more 32 bit offsets, then:
|
|
* That subgraph can be treated as an independent unit and all nodes of the subgraph packed in isolation
|
|
from the rest of the graph.
|
|
* In a table that occupies less than 4gb of space (in practice all fonts), that packed independent
|
|
subgraph can be placed anywhere after the parent nodes without overflowing the 32 bit offsets from
|
|
the parent nodes.
|
|
|
|
The sorting algorithm incorporates this via a "space" modifier that can be applied to nodes in the
|
|
graph. By default all nodes are treated as being in space zero. If a node is given a non-zero space, n,
|
|
then the computed distance to the node will be modified by adding `n * 2^32`. This will cause that
|
|
node and it's descendants to be packed between all nodes in space n-1 and space n+1. Resulting in a
|
|
topological sort like:
|
|
|
|
```
|
|
| space 0 subtables | space 1 subtables | .... | space n subtables |
|
|
```
|
|
|
|
The assign_spaces() step in the high level algorithm is responsible for identifying independent
|
|
subgraphs and assigning unique spaces to each one. More information on the space assignment can be
|
|
found in the next section.
|
|
|
|
# Graph Preprocessing
|
|
|
|
For certain table types we can preprocess and modify the graph structure to reduce the occurences
|
|
of overflows. Currently the repacker implements preprocessing only for GPOS and GSUB tables.
|
|
|
|
## GSUB/GPOS Table Splitting
|
|
|
|
The GSUB/GPOS preprocessor scans each lookup subtable and determines if the subtable's children are
|
|
so large that no overflow resolution is possible (for example a single subtable that exceeds 65kb
|
|
cannot be pointed over). When such cases are detected table splitting is invoked:
|
|
|
|
* The subtable is first analyzed to determine the smallest number of split points that will allow
|
|
for successful offset overflow resolution.
|
|
|
|
* Then the subtable in the graph representation is modified to actually perform the split at the
|
|
previously computed split points. At a high level splits are done by inserting new subtables
|
|
which contain a subset of the data of the original subtable and then shrinking the original subtable.
|
|
|
|
Table splitting must be aware of the underlying format of each subtable type and thus needs custom
|
|
code for each subtable type. Currently subtable splitting is only supported for GPOS subtable types.
|
|
|
|
## GSUB/GPOS Extension Lookup Promotion
|
|
|
|
In GSUB/GPOS tables lookups can be regular lookups which use 16 bit offsets to the children subtables
|
|
or extension lookups which use 32 bit offsets to the children subtables. If the sub graph of all
|
|
regular lookups is too large then it can be difficult to find an overflow free configuration. This
|
|
can be remedied by promoting one or more regular lookups to extension lookups.
|
|
|
|
During preprocessing the graph is scanned to determine the size of the subgraph of regular lookups.
|
|
If the graph is found to be too big then the analysis finds a set of lookups to promote to reduce
|
|
the subgraph size. Lastly the graph is modified to convert those lookups to extension lookups.
|
|
|
|
# Offset Resolution Strategies
|
|
|
|
## Space Assignment
|
|
|
|
The goal of space assignment is to find connected subgraphs that are only reachable via 32 bit offsets
|
|
and then assign each such subgraph to a unique non-zero space. The algorithm is roughly:
|
|
|
|
1. Collect the set, `S`, of nodes that are children of 32 bit offsets.
|
|
|
|
2. Do a directed traversal from each node in `S` and collect all encountered nodes into set `T`.
|
|
Mark all nodes in the graph that are not in `T` as being in space 0.
|
|
|
|
3. Set `next_space = 1`.
|
|
|
|
4. While set `S` is not empty:
|
|
|
|
a. Pick a node `n` in set `S` then perform an undirected graph traversal and find the set `Q` of
|
|
nodes that are reachable from `n`.
|
|
|
|
b. During traversal if a node, `m`, has a edge to a node in space 0 then `m` must be duplicated
|
|
to disconnect it from space 0.
|
|
|
|
d. Remove all nodes in `Q` from `S` and assign all nodes in `Q` to `next_space`.
|
|
|
|
|
|
c. Increment `next_space` by one.
|
|
|
|
|
|
## Manual Iterative Resolutions
|
|
|
|
For each overflow in each iteration the algorithm will attempt to apply offset overflow resolution
|
|
strategies to eliminate the overflow. The type of strategy applied is dependent on the characteristics
|
|
of the overflowing link:
|
|
|
|
* If the overflowing offset is inside a space other than space 0 and the subgraph space has more
|
|
than one 32 bit offset pointing into the subgraph then subdivide the space by moving subgraph
|
|
from one of the 32 bit offsets into a new space via the duplication of shared nodes.
|
|
|
|
* If the overflowing offset is pointing to a subtable with more than one incoming edge: duplicate
|
|
the node so that the overflowing offset is pointing at it's own copy of that node.
|
|
|
|
* Otherwise, attempt to move the child subtable closer to it's parent. This is accomplished by
|
|
raising the priority of all children of the parent. Next time the topological sort is run the
|
|
children will be ordered closer to the parent.
|
|
|
|
# Test Cases
|
|
|
|
The harfbuzz repacker has tests defined using generic graphs: https://github.com/harfbuzz/harfbuzz/blob/main/src/test-repacker.cc
|
|
|
|
# Future Improvements
|
|
|
|
Currently for GPOS tables the repacker implementation is sufficient to handle both subsetting and the
|
|
general case of font compilation repacking. However for GSUB the repacker is only sufficient for
|
|
subsetting related overflows. To enable general case repacking of GSUB, support for splitting of
|
|
GSUB subtables will need to be added. Other table types such as COLRv1 shouldn't require table
|
|
splitting due to the wide use of 24 bit offsets throughout the table.
|
|
|
|
Beyond subtable splitting there are a couple of "nice to have" improvements, but these are not required
|
|
to support the general case:
|
|
|
|
* Extension demotion: currently extension promotion is supported but in some cases if the non-extension
|
|
subgraph is underfilled then packed size can be reduced by demoting extension lookups back to regular
|
|
lookups.
|
|
|
|
* Currently only children nodes are moved to resolve offsets. However, in many cases moving a parent
|
|
node closer to it's children will have less impact on the size of other offsets. Thus the algorithm
|
|
should use a heuristic (based on parent and child subtable sizes) to decide if the children's
|
|
priority should be increased or the parent's priority decreased.
|