NAME
Data::NDArray::Shared - shared-memory typed N-dimensional numeric array for Linux
SYNOPSIS
use Data::NDArray::Shared;
# a 2x3 array of doubles in an anonymous shared mapping
# ($path = undef for an anonymous array)
my $a = Data::NDArray::Shared->new(undef, "f64", 2, 3);
$a->ndim; # 2
$a->size; # 6 (== 2 * 3, also ->numel)
$a->shape; # (2, 3)
$a->strides; # (3, 1) row-major, in elements
$a->dtype; # "f64"
$a->itemsize; # 8
$a->set(0, 0, 1.5); # element [0][0] = 1.5 (multi-index)
$a->get(0, 0); # 1.5
$a->set_flat(5, 9); # last element by flat index
$a->get_flat(5); # 9
$a->fill(7); # every element = 7
$a->zero; # every element = 0
$a->sum; $a->mean; $a->min; $a->max; # whole-array reductions
$a->add_scalar(2); # every element += 2 (in place)
$a->mul_scalar(3); # every element *= 3 (in place)
$a->reshape(3, 2); # same data, shape (3,2), strides (2,1)
# element-wise array arithmetic (same dtype + total size), in place
my $b = Data::NDArray::Shared->new(undef, "f64", 3, 2);
$a->add($b); # a[i] += b[i]
$a->subtract($b); # a[i] -= b[i]
$a->multiply($b); # a[i] *= b[i]
my $list = $a->to_list; # arrayref of all elements, row-major
# integer dtypes: i64/i32/i16/i8/u64/u32/u16/u8
my $c = Data::NDArray::Shared->new(undef, "u8", 4);
$c->set_flat(0, 300); # wraps to 44 (stored in the element width)
# share across processes via a backing file ($path = the file)
my $shared = Data::NDArray::Shared->new("/tmp/nd.bin", "f64", 100, 100);DESCRIPTION
A dense, row-major numeric tensor in shared memory, shared across processes. The array has a fixed dtype (one of f64, f32, i64, i32, i16, i8, u64, u32, u16, u8), a fixed shape of 1 to 8 dimensions, and the matching row-major strides (in elements). The elements live contiguously in a shared mapping, so several processes share one array: any process that opens the same backing file, inherits the anonymous mapping across fork, or reopens a passed memfd, sees the same data.
Supported operations:
Indexed access --
get(@idx)/set(@idx, $val)by a full multi-index, andget_flat($e)/set_flat($e, $val)by a single linear (row-major) index0 .. size-1.Bulk fills --
fill($val)sets every element;zerosets every element to zero.reshape(@newshape) -- change the shape without copying data; the total element count must be unchanged. Strides are recomputed row-major.
Reductions --
sum,mean(both return a floating-point number computed by double accumulation),minandmax(return the actual extreme element in the dtype-correct type).In-place scalar arithmetic --
add_scalar($s)andmul_scalar($s)applyelement OP $sto every element.In-place element-wise array arithmetic --
add,subtractandmultiplycombine the receiver with anotherData::NDArray::Sharedof the same dtype and same total size, element by element.
Values are stored in the element type. For the integer dtypes, a value that does not fit the element width wraps/truncates to that width per C cast rules (storing 300 into a u8 yields 44); the caller is responsible for fitting values to the dtype. Float dtypes store the nearest representable value (f32 loses precision relative to a Perl NV). All arithmetic on integer dtypes is performed in the element's integer type (so it can overflow/wrap); float dtypes accumulate reductions in double.
A write-preferring futex rwlock with dead-process recovery guards every mutation, so writes from many processes serialize cleanly. The immutable header fields (dtype, ndim, size, itemsize, shape, strides) are read without locking (reshape updates shape/strides/ndim under the write lock). Linux-only. Requires 64-bit Perl.
METHODS
Constructors
my $a = Data::NDArray::Shared->new($path, $dtype, @shape); # file-backed
my $a = Data::NDArray::Shared->new(undef, $dtype, @shape); # anonymous
my $a = Data::NDArray::Shared->new_memfd($name, $dtype, @shape);
my $a = Data::NDArray::Shared->new_memfd(undef, $dtype, @shape);
my $a = Data::NDArray::Shared->new_from_fd($fd);$path is the backing file (undef for an anonymous mapping); $dtype is the dtype name (f64, i32, ...); and @shape is the shape: ($path, $dtype, @shape). new_memfd takes the memfd label as its leading argument instead of a path (undef for an unnamed memfd): ($name, $dtype, @shape).
@shape must have 1 to 8 dimensions, each >= 1. The constructor croaks on an unknown dtype, on no dimensions or a zero/negative dimension, on more than 8 dimensions, or if the implied data buffer (product(shape) * itemsize) would overflow or exceed an internal 1 TiB cap (shape too large). A freshly created array is zero-filled.
When reopening an existing file or memfd, the stored dtype, shape and strides win and the existing data is preserved; the dtype/shape you pass to new on a reopen are only used when the file is brand new. new_memfd creates a Linux memfd (transferable via its memfd descriptor); new_from_fd reopens one in another process.
Element access
my $v = $a->get(@idx); # element at the full multi-index
$a->set(@idx, $val); # write the element at the multi-index
my $v = $a->get_flat($e); # element at flat (row-major) index $e
$a->set_flat($e, $val); # write the element at flat index $eget/set take exactly ndim indices; each index must be in 0 .. shape[d]-1. The flat index for get_flat/set_flat must be in 0 .. size-1. A wrong index count or an out-of-range index croaks before any lock is taken (so a caught croak never leaks a lock). get and get_flat return the dtype-correct scalar (a floating-point number for float dtypes, a signed integer for the signed-int dtypes, an unsigned integer for the unsigned-int dtypes). set/set_flat store the value in the element type, wrapping integer values to the element width (see "DESCRIPTION").
Indices must be non-negative integers in 0 .. shape-1; a negative index is treated as a large unsigned value and croaks out of range.
Bulk fills
$a->fill($val); # every element = $val (returns $a)
$a->zero; # every element = 0 (returns $a)fill writes the typed value of $val to every element (integers wrap to the element width). zero sets the whole buffer to zero. Both return the array for chaining.
reshape
$a->reshape(@newshape); # returns $areshape changes the shape in place without moving any data: the flat, row-major sequence of elements is unchanged; only shape, strides and ndim are updated (strides recomputed row-major). The product of @newshape must equal the current size, and the new rank must be 1 to 8; otherwise it croaks. Returns the array for chaining.
Reductions
my $s = $a->sum; # floating-point sum (double accumulation)
my $m = $a->mean; # $s / size
my $lo = $a->min; # smallest element, dtype-correct
my $hi = $a->max; # largest element, dtype-correctsum and mean always return a floating-point number: every element is read as a double and accumulated, so for the 64-bit integer dtypes a very large sum may lose integer precision. min and max return the actual extreme element value in its native dtype (so an i64 min is exact). The array always has at least one element, so these never operate on an empty array.
Scalar arithmetic (in place)
$a->add_scalar($s); # element += $s for every element
$a->mul_scalar($s); # element *= $s for every elementEach applies the operation to every element in the element's own arithmetic: float dtypes compute in floating point; integer dtypes compute in the element's integer type (and therefore wrap on overflow). Both return the array for chaining.
Element-wise array arithmetic (in place)
$a->add($b); # a[i] += b[i]
$a->subtract($b); # a[i] -= b[i]
$a->multiply($b); # a[i] *= b[i]Each combines the receiver with another Data::NDArray::Shared element by element, storing the result back into the receiver. The other array must have the same dtype and the same total size (its shape need not match, only the element count); a mismatch croaks before any lock is taken. Self-application is allowed and meaningful: $a->add($a) doubles, $a->subtract($a) zeroes, $a->multiply($a) squares. Each returns the receiver for chaining.
Locking is deadlock-free across processes: the two arrays' locks are acquired in a globally consistent order keyed on a per-array shared identity, with the receiver taking the write lock and the other the read lock. Two unrelated processes performing X->add(Y) and Y->add(X) concurrently cannot deadlock.
Whole-array list
my $aref = $a->to_list; # arrayref of all elements, row-major
my $aref = $a->flat; # alias for to_listto_list (aliased flat) returns a new array reference holding every element in flat row-major order, each as the dtype-correct scalar.
Accessors
$a->dtype; # dtype name string, e.g. "f64"
$a->ndim; # number of dimensions
$a->size; # total element count (also ->numel)
$a->itemsize; # bytes per element
$a->shape; # list of dimension sizes
$a->strides; # list of row-major strides (in elements)All read immutable (or reshape-updated) header fields. size (aliased numel) and itemsize never change; shape/strides/ndim change only under reshape.
Lifecycle
$a->path; $a->memfd; $a->sync; $a->unlink; # or Class->unlink($path)sync flushes the mapping to its backing store (a no-op for anonymous and memfd arrays, which have none); unlink removes the backing file (also callable as Class->unlink($path)); path returns the backing path (undef for anonymous, memfd, or fd-reopened arrays); memfd returns the backing descriptor -- the memfd of a new_memfd array or the dup'd fd of a new_from_fd array, and -1 for file-backed or anonymous arrays.
STATS
stats() returns a hashref describing the array:
dtype-- the dtype name string.ndim-- the number of dimensions.size-- the total element count.itemsize-- bytes per element.shape-- an arrayref of the dimension sizes.ops-- running count of operations that took the write lock (everyset,set_flat,fill,zero,reshape,add_scalar,mul_scalar,add,subtract,multiply).mmap_size-- bytes of the shared mapping.
PDL INTEROP
If PDL is installed the array converts to and from PDL ndarrays. PDL is an optional, load-on-demand dependency -- there is no build- or runtime prereq; the four conversion methods (to_pdl, from_pdl, update_from_pdl, as_pdl_alias) croak if PDL is missing, while buffer and update_from_bytes have no PDL dependency. Each dtype maps to a PDL type of the same byte width (f64 to double, i32 to long, u64 to ulonglong, and so on), so the data moves with no per-element conversion.
Axis order: this array is row-major (C-order) while PDL's dim(0) is the fastest-varying axis, so the shape is reversed across the boundary -- an ($r, $c) array corresponds to PDL dims ($c, $r), and $piddle->at($j, $i) is $array->get($i, $j). The conversion methods handle this for you.
$piddle = $array->to_pdlA new piddle holding a copy of the data, of the mapped PDL type and dims
reverse($array->shape). Read under the lock, so it is a consistent snapshot.$array = Data::NDArray::Shared->from_pdl($piddle, $path)A new shared array copied from
$piddle(made physical and contiguous first); the dtype and shape follow the piddle's type andreverseof its dims.$pathis the backing file (undefor omitted for an anonymous mapping).$array->update_from_pdl($piddle)Copy
$piddleinto this array in place (write-locked). The piddle's type must match the dtype and its dims must equalreverse($array->shape), else it croaks. Returns the array.$piddle = $array->as_pdl_aliasA piddle that aliases the shared mapping with no copy (a real
PDL_DONTTOUCHDATAndarray over our memory): an in-place PDL operation ($p .= ...,$p->inplace->...) writes straight through to shared memory -- visible to every process that maps it -- and reads see live data. The array is kept alive for as long as the piddle.This one method needs PDL at build time (it is compiled against PDL's C API): if the module was installed without PDL present it
croaks, while the copy methods above keep working through a runtimerequire PDL. Reinstall with PDL installed to enable it.Caveats. The alias bypasses the rwlock: you must coordinate access yourself (no other process mutating concurrently), as with any unlocked shared-memory view. Do not resize or retype the alias (a reshape that grows it, a type conversion) -- it is a fixed window onto the mapping; use
to_pdl/from_pdlwhen you want an independent, resizable copy.$bytes = $array->bufferThe raw contiguous data region as a byte string (read-locked snapshot), row-major C-order -- useful on its own for serialization or IPC, and the basis for
to_pdl.$array->update_from_bytes($bytes)is the inverse (write-locked; the string must be exactlysize * itemsizebytes).
See eg/pdl_interop.pl for a worked example, including a cross-process PDL transform on one shared array.
SHARING ACROSS PROCESSES
The array lives in a shared mapping, shared the same three ways as the rest of the family: a backing file (every process calls new($path, $dtype, @shape) on the same path), an anonymous mapping inherited across fork, or a memfd whose descriptor is passed to an unrelated process (over a UNIX socket via SCM_RIGHTS, or via /proc/$pid/fd/$n) and reopened with new_from_fd($fd). Because the mapping is shared, every process reads and writes the same elements. All mutation is serialized by the write lock, so a set of disjoint writers produces a well-defined final array regardless of how they interleave.
# parent and children fill disjoint slices of one shared array
my $a = Data::NDArray::Shared->new(undef, "f64", 4000); # before fork
unless (fork) { $a->set_flat($_, $_) for 0 .. 999; exit }
wait;
print $a->get_flat(500), "\n"; # reflects the child's writesSECURITY
The mmap region is writable by all processes that open it. Do not share backing files with untrusted processes.
CRASH SAFETY
Mutation is guarded by a futex-based write-preferring rwlock with PID-encoded ownership; if a holder dies, the next contender detects the dead owner and recovers. Because each mutation updates the data buffer (and, for reshape, a few header words) while holding the lock, a crash leaves the array consistent up to the last completed operation. Limitation: PID reuse is not detected (very unlikely in practice).
SEE ALSO
Data::Histogram::Shared, Data::RoaringBitmap::Shared, Data::DisjointSet::Shared, Data::CountMinSketch::Shared, Data::HyperLogLog::Shared, Data::BloomFilter::Shared, Data::Intern::Shared, Data::SortedSet::Shared, Data::SpatialHash::Shared, and the rest of the Data::*::Shared family.
AUTHOR
vividsnow
LICENSE
This is free software; you can redistribute it and/or modify it under the same terms as Perl itself.