Data Structure Descriptors
Contents
Data Structure Descriptors¶
Data Structure Descriptors (DSDs) are a compact representation of a (possibly non-contiguous) chunk of memory or a sequence of incoming or outgoing wavelets. Combined with DSD operations, DSDs enable various repeated operations to be expressed using just one hardware instruction.
Basic Syntax¶
DSDs are defined in CSL using the following syntax:
@get_dsd(dsd_type, properties);
Where:
dsd_type
is one ofmem1d_dsd
,mem4d_dsd
,fabin_dsd
, orfabout_dsd
.properties
is a struct that specifies auxiliary properties of the particular DSD type.
Different DSD types require different properties.
One-Dimensional Memory Vectors¶
The mem1d_dsd
type is used to encode a memory vector using a single
induction variable. Memory vectors are configured using the following fields:
base_address
, any expression of pointer type.extent
, any expression of typeu16
.stride
, any expression of typei8
. (optional, defaults to 1).offset
, any expression of typei16
. (optional, defaults to zero).tensor_access
, a comptime-known tensor access expression (see tensor_access).wavelet_index_offset
, a comptime-known boolean expression (optional, defaults tofalse
).
tensor_access¶
The tensor_access
field is a convenient grouping of properties that
fully specifies a memory access pattern through an expression that is
referred to as a tensor access expression. A tensor access expression
has the following syntax:
|<induction-variable>| {<length>} -> <base-address>[<expr>]
Where:
induction-variable
, a single identifier that represents the loop induction variable (its iteration variable).length
, a comptime-known non-negative integer expression that represents the number of times to iterate.base-address
, the name of a variable of tensor type or the name of a comptime-known variable of pointer-to-tensor type.<expr>
, a comma-separated list of affine expressions of the loop iteration variable and comptime-known values. There must be exactly as many affine expressions as the number of dimensions of the tensor that is specified bybase-address
.
For example:
const array = @zeros([10]u16);
const tenWords = @get_dsd(mem1d_dsd, .{
.tensor_access = |i|{10} -> array[i]
});
In the above snippet, tenWords
is a mem1d_dsd
specifying accesses to
array
at indices 0 through 9.
A tensor access expression can be used to refer to odd elements of an array:
const array = @zeros([10]u16);
const oddElements = @get_dsd(mem1d_dsd, .{
.tensor_access = |i|{5} -> array[2 * i + 1]
});
It can also be used to refer to a single element of the array:
const array = @zeros([10]u16);
const firstElement = @get_dsd(mem1d_dsd, .{
.tensor_access = |i|{10} -> array[0]
});
Such a pattern is often useful in reduction operations.
Although mem1d_dsd
allows only one induction variable, the underlying array
can still be a multidimensional array. For instance, the following mem1d
DSD refers to the diagonal elements of a 2D (20x20) array.
const array = @zeros([20,20]u16);
const diagonal = @get_dsd(mem1d_dsd, .{
.tensor_access = |i|{20} -> array[i,i]
});
The tensor access expression is syntactic sugar to create an anonymous struct with the following comptime-known fields:
base_address
, a pointer representing the base address of the underlying access pattern.offset
, an expression of typei16
that is the access pattern’s offset frombase_address
.stride
, a tuple containing a single expression of type ‘i8’.extent
, a tuple containing a single expression of type ‘u16’.
This also means that the type of a tensor access expression is that of the
corresponding anonymous struct which can be coerced to a comptime_struct
.
For example:
var A: [10]i16;
// 'access_of_A' is exactly equivalent to:
// .{.base_address = &A, .offset = 42, .stride = .{2}, .extent = .{10}}
const access_of_A: comptime_struct = |i|{10} -> A[2*i + 42];
// A 'mem1d_dsd' created through the 'tensor_access' property.
const dsd1 = @get_dsd(mem1d_dsd, .{.tensor_access = access_of_A});
// A 'mem1d_dsd' created through explicitly specifying properties
// individually.
const dsd2 = @get_dsd(mem1d_dsd, .{.base_address = access_of_A.base_address,
.offset = access_of_A.offset,
.stride = access_of_A.stride,
.extent = access_of_A.extent});
In the example above, both ways of creating a 1D memory DSD are equivalent,
which means that dsd1
and dsd2
are exactly the same.
As a result, it is also possible to use an anonymous struct directly as
the value of the tensor_access
field, as follows:
var A: [10]i16;
// The '.offset' field defaults to zero.
const access_of_A = .{.base_address = &A,
.stride = 2,
.extent = 10};
const dsd = @get_dsd(mem1d_dsd, .{.tensor_access = access_of_A});
It is not allowed to specify any DSD properties twice, which means that
the base_address
, stride
, extent
and offset
fields cannot
be specified in both the tensor_access
value and as top-level properties
at the same time.
Runtime mem1d_dsd
tensor access properties¶
By specifying memory access properties of 1D memory DSDs individually, we are able to use runtime values for them. This is not possible through the tensor access expression since they must be comptime-known.
For example:
var ptr: [*]i16;
task foo(stride: i16, len: u16) void {
// Definition of a 'mem1d_dsd' with runtime properties.
var dsd = @get_dsd(mem1d_dsd, .{.base_address = ptr,
.stride = @as(i8, stride),
.extent = len});
}
wavelet_index_offset¶
The wavelet_index_offset
field expects a comptime-known boolean value that
indicates whether the wavelet_index_offset
mode is enabled.
If the wavelet_index_offset
mode is enabled, the address of the underlying
memory buffer is incremented by the index
specified in the DSD operation as
explained in Explicit Index Offset.
If a DSD with wavelet_index_offset
enabled is used in a DSD operation, the
DSD operation must provide an index field. Otherwise, the behavior of the
respective DSD operation is undefined.
const array = @zeros([size]u16);
const memDSD = @get_dsd(mem1d_dsd, .{
.tensor_access = |i|{10} -> array[i],
.wavelet_index_offset = true
});
task my_task() void {
// The addition will start at an offset specified
// by 'my_index'.
@add16(memDSD, memDSD, data, .{.index = my_index});
// The behavior of this builtin is undefined.
@add16(memDSD, memDSD, data);
}
Two-, Three-, or Four-Dimensional Memory Vectors¶
The mem4d_dsd
is a DSD type that is used to refer to multi-dimensional
memory vectors, up to a maximum of four dimensions. Multi-dimensional memory
vectors are configured using the following fields:
base_address
, a comptime-known pointer to a tensor.offset
, any expression of typei16
(optional, defaults to zero).stride
, a comptime-known tuple (i.e., anonymous struct with nameless fields) of expressions of typei16
. (opional, defaults to a tuple with values of 1 that has the same size as theextent
tuple).extent
, a comptime-known tuple (i.e., anonymous struct with nameless fields) of expressions of typeu16
.tensor_access
, a tensor access expression (see tensor_access).wavelet_index_offset
, a comptime-known boolean expression (optional, defaults tofalse
).
tensor_access¶
Like in 1D memory DSDs, the tensor_access
field is a convenient grouping of
properties through a tensor access expression. The only difference is that
in multi-dimensional memory DSDs we can have up to 4 comma-seprated induction
variables and length expressions and the number of induction
variables and length expressions must match. For example:
const array = @zeros([4,3]u16);
const subset = @get_dsd(mem4d_dsd, .{
.tensor_access = |i,j|{2,2} -> array[i, j]
});
The following, more complicated, example shows a DSD that uses all four dimensions with non-zero offsets.
const array = @zeros([1,2,3,4]u16);
const subset = @get_dsd(mem4d_dsd, .{
.tensor_access = |i,j,k,l|{1,2,1,4} -> array[i, j, 1+k, l]
});
mem4d
DSDs can be used with single-dimensional vectors as well, like in the
following, somewhat contrived, example:
const subset = @get_dsd(mem4d_dsd, .{
.tensor_access = |i,j,k,l|{1,1,1,1} -> array[i + j + k + l]
});
Like 1D memory DSDs the tensor access expression is lowered into an anonymous struct with the same fields (see tensor_access). For example:
var A: [4, 5]i16;
// 'access_of_A' is exactly equivalent to:
// .{.base_address = &A, .offset = 2,
// .stride = .{1,-3,-3,-23}, .extent = .{5,5,5,5}}
const access_of_A = |i, j, k, l|{5, 5, 5, 5} -> A[i + j, k + l + 2];
// A 'mem4d_dsd' created through the 'tensor_access' property.
const dsd1 = @get_dsd(mem4d_dsd, .{.tensor_access = access_of_A});
// A 'mem4d_dsd' created through explicitly specifying properties
// individually.
const dsd2 = @get_dsd(mem4d_dsd, .{.base_address = access_of_A.base_address,
.offset = access_of_A.offset,
.stride = access_of_A.stride,
.extent = access_of_A.extent});
wavelet_index_offset¶
See wavelet_index_offset.
Pointers To Scalars As Destinations¶
Some DSD operations support pointers to scalars as destination arguments. These operations essentially behave as if the destination were a memory DSD with zero stride, whose destination is a one-element array whose data is stored at the pointer. For example:
const src_array = [8]f16{ 0, 1, 2, 3, 4, 5, 6, 7 };
// src_dsd will access src_array at indices, 0, 2, 4, and 6.
const src_dsd = @get_dsd(mem1d_dsd, .{
.tensor_access = |i|{4} -> src_array[2*i]
});
const dst_array = @zeros([1]f16);
// Because dst_dsd has zero stride (`i` is never mentioned to the right of
// the arrow in the tensor access expression), the @fmovh below will first
// move 0, then 2, then 4, then 6 into dst_array[0]. Thus afterwards,
// dst_array[0] will have a value of 6.
const dst_dsd = @get_dsd(mem1d_dsd, .{
.tensor_access = |i|{4} -> dst_array[0]
});
@fmovh(dst_array, src_dsd);
@assert(dst_array[0] == 6);
// An @fmovh operation with a pointer to scalar as its destination behaves
// similarly, so the value of dst_scalar after the following @fmovh will
// also be 6.
const dst_scalar: f16 = 0;
@fmovh(&dst_scalar, src_dsd);
@assert(dst_scalar == 6);
Fabric Input Vectors¶
The fabin_dsd
DSD type is used to refer to wavelets arriving at the PE from
the fabric. Fabric input vectors are configured using the following two fields.
fabric_color
, which specifies the color of the wavelets to associate with this vectorextent
, which specifies the number of wavelets that this vector refers to
For instance, the following DSD refers to 5 wavelets expected to arrive on color
trigger
.
const inDsd = @get_dsd(fabin_dsd, .{ .extent = 5, .fabric_color = trigger });
Fabric Output Vectors¶
Fabric output vectors, specified using the fabout_dsd
type, are configured
similarly to fabric input (fabin_dsd
) vectors, with the exception that
fabric output vectors may contain the following additional fields:
control
wavelet_index_offset
control¶
The control
field expects a comptime-known boolean expression, which is used
to signify control wavelets.
For instance, the following DSD refers to 1024 non-control wavelets to be sent
along the color tx
.
const outDsd = @get_dsd(fabout_dsd, .{ .extent = 1024, .fabric_color = tx });
Whereas the following DSD refers to a single control wavelet to be sent along
the color out
.
const dsd = @get_dsd(fabout_dsd, .{
.extent = 1,
.control = true,
.fabric_color = out,
});
wavelet_index_offset¶
The wavelet_index_offset
field expects a comptime-known boolean expression,
which is used to enable the wavelet_index_offset
mode. When this mode is
enabled, the outgoing wavelets will carry a fixed index field specified by the
user per-operation as explained in Explicit Index Offset.
Similar to the semantics of memory DSDs, if the operations that use fabric
output DSDs with wavelet_index_offset
enabled do not specify an index
value, then the behavior is undefined.
const outDSD = @get_dsd(fabout_dsd, .{
.extent = 1,
.fabric_color = out,
.wavelet_index_offset = true,
});
task my_task() void {
// The outgoing wavelets will have 'my_index' stored in
// their high 16-bits.
@add16(outDSD, memDSD, 42, .{.index = my_index});
// The behavior of this builtin is undefined.
@add16(outDSD, memDSD, 42);
}
FIFOs¶
A FIFO DSD is a kind of DSD that uses a memory region to create a First-In First-Out buffer.
To create a FIFO DSD, the @allocate_fifo
builtin is used:
var fifo_buffer = @zeros([32]i16);
const fifo = @allocate_fifo(fifo_buffer);
The @allocate_fifo
builtin must be associated with a const
variable in
the global scope. The argument to @allocate_fifo
must be a global array or
pointer to a global array. This array must be marked as var
and must have
elements of type i16
, u16
, f16
, i32
, u32
or f32
.
If the fifo buffer (i.e., the argument to @allocate_fifo
) was declared
without an explicit alignment requirement (by using the align
) directive
(see Variables) then the compiler will force its alignment to be the
minimum alignment that is required for fifos on the target architecture.
On the other hand, if the fifo buffer has been declared with an explicit alignment requirement that is less than the minimum alignment required for fifo buffers on the target architecture, an error will be raised.
Note that if the fifo buffer is declared as extern
(see Variables)
without an explicit align
directive then a warning will be emitted
indicating that proper alignment must be specified for the respective
buffer definition. This warning can be suppressed by specifying an explicit
alignment requirement to the extern
fifo buffer declaration.
Allocating a FIFO consumes hardware resources for the duration of the program, as such they should be used sparingly.
The following restrictions apply when using a FIFO DSD in a DSD operation:
The FIFO DSD operand must be comptime-known.
A FIFO cannot be used as an operand to the
@map
builtin.If a DSD operation uses more than one source operand:
at most one operand may be a FIFO DSD, and
the FIFO DSD operand must not be the first (left-most) source operand.
An asynchronous DSD operation that reads from an empty FIFO will be suspended until the FIFO receives an element.
An asynchronous DSD operation that writes to a full FIFO will be suspended until the FIFO is not full.
A non-asynchronous DSD operation that reads from an empty FIFO will terminate
and return false
. The length of the FIFO will be updated to the remaining
length after the FIFO became empty. If the destination operand is a pointer to
a scalar, any data popped from the FIFO during the operation will be
discarded, and the value stored at the pointer will remain unchanged.
A non-asynchronous DSD operation that writes to a full FIFO will terminate
and return false
. The length of the FIFO will be updated to the remaining
length after the FIFO became full.
FIFOs are typically used with a pair of DSD operations: one operation writing elements to the FIFO and one operation reading elements from the FIFO. For example:
@mov16(fifo, ...); // Write to the FIFO
@mov16(..., fifo); // Read from the FIFO
Task Activation on Pop and Push¶
The @allocate_fifo
builtin takes an optional configuration struct with two
fields, both optional.
The .activate_pop
field specifies a local_task_id
or comptime-known
task name to be activated on pop from the FIFO.
The .activate_push
field specifies a local_task_id
or comptime-known
task name to be activated on push to the FIFO.
The associated task must be bound as a local task.
Note that the specified .activate_pop
task is only activated on pop if the
FIFO has previously hit a FIFO full event, and if the pop causes the FIFO to
transition from having insufficient free space to having sufficient free space,
where “sufficient free space” means sufficient space for the push operation
that originally triggered the FIFO full event to proceed. The amount of space
required depends on the operand size and SIMD width of the push operation that
previously triggered the FIFO full event.
Similar rules apply in the other direction: the .activate_push
task is only
activated on push if the FIFO has previously hit a FIFO empty event, and if the
push causes the FIFO to transition from having insufficient data to having
sufficient data, where “sufficient data” means sufficient data in the queue for
the pop operation that originally triggered the FIFO empty event to proceed.
task on_push() void { ... }
task on_pop() void { ... }
var fifo_buffer = @zeros([32]i16);
const fifo = @allocate_fifo(
fifo_buffer,
.{ .activate_pop = on_pop, .activate_push = on_push }
);
Changing FIFO Properties¶
The following builtins can be used to change the properties of a FIFO at
runtime. Changing FIFO properties at comptime will be enabled in the future
through the FIFO initialization builtin (i.e., @allocate_fifo
).
As was mentioned earlier, FIFOs acquire hardware resources for the duration
of the program and therefore updating the properties of FIFOs happens in-place
by directly accessing these hardware resources without creating new DSD
values as is the case for the rest of the DSD kinds.
@set_fifo_read_length and @set_fifo_write_length¶
Update the length field of a FIFO that is associated with a read or write operation respectively.
Syntax¶
@set_fifo_read_length(fifo, length);
@set_fifo_write_length(fifo, length);
Where:
fifo
is a comptime-known FIFO DSD expression.length
is a 16-bit unsigned integer expression that specifies the length to be applied in number of FIFO elements.
Example¶
var fifo_buffer = @zeros([32]i16);
// FIFOs are always initialized with read/write length zero.
const fifo = @allocate_fifo(fifo_buffer);
const fifo_length = 42;
// Sets the FIFO write length before a write operation.
@set_fifo_write_length(fifo, fifo_length);
@mov16(fifo, ...);
// Sets the FIFO read length before a read operation.
@set_fifo_read_length(fifo, fifo_length);
@move(..., fifo);
Semantics¶
The builtin will update the read or write length of the input FIFO in-place by modifying the underlying hardware resource directly.
Changing DSD Properties¶
The following builtins can be used to change DSD properties at runtime or comptime. All of these builtins will always result in a new DSD value while the input value remains unchanged.
@set_dsd_base_addr¶
Create a new memory DSD value based on the input memory DSD value and base address.
Syntax¶
@set_dsd_base_addr(input_dsd, base_addr);
Where:
input_dsd
is a memory DSD expression, i.e., a DSD expression with a type that is eithermem1d_dsd
ormem4d_dsd
.base_addr
is a tensor identifier or a pointer expression whose base-type is a tensor.
Example¶
var A = @zeros([10]i16);
// Create a new DSD that is a clone of 'input_dsd' but has
// 'A' as its base-address.
var dsd1 = @set_dsd_base_addr(input_dsd, A);
// Use a pointer expression as the new base-address parameter.
var dsd2 = @set_dsd_base_addr(input_dsd, &A);
Semantics¶
The builtin returns a new memory DSD value that is a clone of the input DSD
value but with the provided base_addr
parameter as the new base address.
The new base address will replace both the base address and offset (if any)
of the input DSD value.
@increment_dsd_offset¶
Create a new memory DSD value based on the input memory DSD value, offset and tensor element type.
Syntax¶
@increment_dsd_offset(input_dsd, offset, elem_type);
Where:
input_dsd
is a memory DSD expression, i.e., a DSD expression with a type that is eithermem1d_dsd
ormem4d_dsd
.offset
is a 16-bit signed integer that specifies the offset to be applied as number of elements ofelem_type
.elem_type
is a type expression that is used to convertoffset
into number of words. It must be a 16-bit or 32-bit numeric type (u16
,i16
,i16
,i32
,f16
, orf32
).
Example¶
const A = @zeros([10, 10]f32);
// dsdA is defined as a 2x2 square that is at a diagonal
// offset within A.
const dsdA = @get_dsd(mem4d_dsd, .{
.tensor_access = |i, j|{2, 2} -> A[i + 1, j + 1]});
// Create a new DSD that is a clone of the 'dsdA' but its
// base address is moved backwards by 10 f32 elements. In
// practice, new_dsd will have moved the 2x2 square upwards
// by one row.
var new_dsd = @increment_dsd_offset(dsdA, -10, f32);
Semantics¶
The builtin returns a new memory DSD value that is a clone of the input DSD
value but with a new base address that is the result of adding the offset
parameter to the base address of the input DSD. The offset
parameter
specifies the number of tensor elements to be added to the input DSD’s base
address. The builtin performs no runtime or comptime checks for out-of-bounds
accesses so the user needs to be aware of such risk.
@set_dsd_length¶
Create a new DSD value based on the input DSD and length.
Syntax¶
@set_dsd_length(input_dsd, length);
Where:
input_dsd
is a DSD expression with any DSD type exceptmem4d_dsd
.length
is a 16-bit unsigned integer that specifies the length to be applied in number of tensor elements or wavelets.
Semantics¶
The builtin returns a new DSD value that is a clone of the input DSD value but with the new length applied.
@set_dsd_stride¶
Create a new 1D memory DSD value based on the input 1D memory DSD and stride.
Syntax¶
@set_dsd_stride(input_dsd, stride);
Where:
input_dsd
is a DSD expression that must be of typemem1d_dsd
.stride
is an 8-bit signed integer that specifies the stride to be applied in number of tensor elements.
Semantics¶
The builtin returns a new DSD value that is a clone of the input DSD value but with the new stride applied.
Asynchronous DSD Operations¶
DSD operations involving fabric operands are allowed to happen asynchronously. This causes a new thread to start executing concurrently with any ongoing tasks and other asynchronous operations. A thread that starts executing as part of an asynchronous DSD operation is referred to as a microthread (see Microthreads).
A DSD operation will happen asynchronously if either of these conditions are true:
At least one DSD operand has a fabric DSD type, that is,
fabin_dsd
orfabout_dsd
, and theasync
configuration is used.At least one DSR operand was loaded using the
async
configuration (see @load_to_dsr).
For example:
// The @mov16 operation will be asynchronous.
@mov16(destination_dsd, source_dsd, .{.async = true});
// The @mov16 will also be asynchronous even though ``async`` is not
// specified by the operation itself.
const source_dsr = @get_dsr(dsr_src0, 0);
@load_to_dsr(source_dsr, my_fabin_dsd, .{.async = true});
// Specifying async here is not strictly necessary,
// but recommended to be explicit about the behavior of the operation.
@mov16(destination_dsd, source_dsr, .{.async = true});
For an operation on a DSR to occur asynchronously, the
DSR must be marked as asynchronous when a DSD is loaded to it with
@load_to_dsr
.
In this case, it is not necessary to specify async
in the DSD operation.
However, it is recommended to do so for clarity and explicitness.
All of the following configuration settings are directly applicable to
DSRs when using the @load_to_dsr
builtin (see @load_to_dsr).
Completion of Asynchronous DSD Operations¶
When an asynchronous DSD operation completes, it may optionally activate or unblock a task. The task to be activated or unblocked is specified in the last argument of the DSD operation.
For example:
@mov16(destination_dsd, source_dsd, .{.async = true, .activate = mytask});
@mov16(destination_dsd, source_dsd, .{.async = true, .unblock = mytask});
At most one of activate
or unblock
may be specified.
The activate
field can be a local_task_id
or a comptime-known task name.
The associated task must be bound as a local task.
The unblock
field can be a:
WSE-2:
color
,data_task_id
,local_task_id
, or comptime-known task name.WSE-3:
input_queue
,data_task_id
,local_task_id
, or comptime-known task name.
As with the .async
field, if using a DSR in an asynchronous operation,
the .activate
and .unblock
fields must be specified
in the @load_to_dsr
call that loads a fabric DSD to the DSR.
For example:
// The @mov16 will also be asynchronous, and my_task_id will
// be activated upon completion.
const source_dsr = @get_dsr(dsr_src0, 0);
@load_to_dsr(source_dsr, my_fabin_dsd,
.{.async = true, .activate = my_task_id});
// Specifying async and activate here is not strictly necessary,
// but recommended to be explicit about the behavior of the operation.
@mov16(destination_dsd, source_dsr,
.{.async = true, .activate = my_task_id});
In this case, as with async
, it is not necessary to specify activate
or unblock
in the DSD operation.
However, it is recommended to do so for clarity and explicitness.
Dynamic Completion Based on Control Wavelets¶
The completion of an asynchronous DSD operation can also be triggered by control
wavelets. This capability must be explicitly enabled through the last argument
of the DSD operation by specifying the on_control
field.
For example:
// The asynchronous DSD operation will terminate.
@mov16(destination_dsd, source_dsd,
.{.async = true, .on_control = .{.terminate = true}});
// The asynchronous DSD operation will terminate and task 'mytask' will be
// activated
@mov16(destination_dsd, source_dsd,
.{.async = true, .on_control = .{.activate = mytask}});
// The asynchronous DSD operation will terminate and task 'mytask' will be
// unblocked
@mov16(destination_dsd, source_dsd,
.{.async = true, .on_control = .{.unblock = mytask}});
The terminate
action requires a boolean expression.
The activate
action requires a local_task_id
or task
name. For activate
, the associated task must be bound as a local task.
The unblock
action requires a:
WSE-2:
color
,data_task_id
,local_task_id
, or task name.WSE-3:
input_queue
,data_task_id
,local_task_id
, or task name.
For unblock
, the associated task must be bound as a data or local task.
Hardware Resources and Asynchronous DSD Operations¶
Asynchronous operations consume two kinds of hardware resources: queues and microthreads. It is the programmer’s responsibility to ensure that concurrent asynchronous DSD operations do not share the same resource (queue or microthread).
Fabric Queues¶
Fabric operands involved in asynchronous DSD operations must be associated with a queue. Input/Output queues are hardware buffers where data is temporarily stored before entering or leaving the compute engine (CE) of a PE.
To specify a queue for fabric input DSDs (fabin_dsd
), the input_queue
attribute must be used, with a value of type input_queue
as the queue
identifier:
const my_fabin_dsd = @get_dsd(fabin_dsd,
.{...,
.input_queue = @get_input_queue(0), ...});
To specify a queue for fabric output DSDs (fabout_dsd
), the output_queue
attribute must be used, with a value of type output_queue
as the queue
identifier:
const my_fabout_dsd = @get_dsd(fabout_dsd,
.{...,
.output_queue = @get_output_queue(0), ...});
The hardware has a finite number of input and output queues, each with different buffering capabilities.
Queue Identifiers |
WSE-2 Input Queue Length (words) |
WSE-2 Output Queue Length (words) |
WSE-3 Input Queue Length (words) |
WSE-3 Output Queue Length (words) |
---|---|---|---|---|
0, 1 |
6 |
2 |
8 |
8 |
2, 3 |
4 |
6 |
4 |
8 |
4, 5 |
2 |
2 |
4 |
8 |
6, 7 |
2 |
N/A |
4 |
8 |
It is the programmer’s responsibility to ensure that no two concurrent DSD operations share an output or input queue:
task t() void {
@mov16(fabric_out_dsd, memory_dsd1, .{ .async = true });
@mov16(fabric_out_dsd, memory_dsd2, .{ .async = true }); // Bad: same
// output queue
}
In the example, two concurrent asynchronous operations are spawned using the
same fabout_dsd
as the destination operand. Therefore, they also use the
same output_queue
, which is invalid.
It is the programmer’s responsibility to ensure that there are no elements in a queue before reusing it for a different operation.
Microthreads¶
Asynchronous DSD operations require a hardware microthread, which is a finite resource.
A hardware microthread is identified by an integer identifier called a microthread ID.
On WSE-2 the microthread ID is implicitly determined by one of the input or output queues involved in the operation:
If a
fabout_dsd
operand is used, the microthread identifier is the same as theoutput_queue
identifier.Otherwise, the microthread identifier is the same as the
input_queue
identifier of the firstfabin_dsd
operand.
It is the programmer’s responsibility to ensure that no two concurrent DSD operations share a microthread.
const fabric_out_dsd = @get_dsd(fabout_dsd,
.{.extent = 10,
.output_queue = @get_output_queue(0)});
const fabric_in_dsd = @get_dsd(fabin_dsd,
.{.extent = 10,
.input_queue = @get_input_queue(0)});
const mem1_dsd = @get_dsd(mem1d_dsd, ...);
const mem2_dsd = @get_dsd(mem1d_dsd, ...);
task t() void {
@mov16(fabric_out_dsd, mem1_dsd, .{ .async = true }); // Microthread ID 0
@mov16(mem2_dsd, fabric_in_dsd, .{ .async = true }); // Bad: same
// Microthread ID!
}
On WSE-3 the user has the option to explicitly specify the microthread ID of a given asynchronous DSD operation. This means that it can be different from the operands’ respective queue IDs (see Microthread IDs).
Microthread Priority¶
The Cerebras hardware supports a priority setting for asynchronous operations. This is also called microthread priority. An asynchronous DSD operation with a fabric input DSD as its destination may have priority specified as follows:
@mov16(destination_dsd, source_dsd,
.{ .async = true, .priority = .{ .high = true });
Valid choices for priority are high
, medium
, and low
(the
default).
In general, the hardware will favor the scheduling of higher-priority
operations when multiple microthreads are running. Priority of the main
thread, i.e., of non-async operations, may also be adjusted. By default,
synchronous operations have a priority between medium
and low
microthreads. See
main_thread_priority for information on
how to adjust the main-thread priority level.
Explicit Index Offset¶
A DSD operation may have an index
configuration field, which is expected to
be an unsigned 16-bit integer value. If this setting is combined with the
wavelet_index_offset
property of memory and/or fabout DSDs, it will have the
following semantics:
Memory DSDs: the
index
value represents a word offset that is added to the base address of the underlying memory buffer.Fabric Output DSDs: the
index
value represents the index that is set to all outgoing wavelets, i.e., all outgoing wavelets will haveindex
set in their high 16-bits.
For example:
const array = @zeros([size]u16);
const memDSD = @get_dsd(mem1d_dsd, .{
.tensor_access = |i|{10} -> array[i],
.wavelet_index_offset = true
});
const outDSD = @get_dsd(fabout_dsd, .{
.extent = 1,
.fabric_color = out,
.wavelet_index_offset = true,
});
task my_task() void {
// The addition will start at an offset specified
// by 'my_index'.
@add16(memDSD, memDSD, 42, .{.index = my_index});
// The outgoing wavelets will have 'my_index' stored in
// their high 16-bits.
@add16(outDSD, memDSD, 42, .{.index = my_index});
}
The index
configuration will be ignored by DSDs that do not have the
wavelet_index_offset
property enabled.
Advanced DSD Features¶
SIMD Mode¶
When using 16-bit values with fabric DSDs, it is possible to send or receive more than one value in a single wavelet using the so-called SIMD mode. The following code block shows how to use SIMD-32 mode with a fabric output DSD.
const out_dsd = @get_dsd(fabout_dsd, .{
.extent = 10,
.fabric_color = out_color,
.simd_mode = .{ .simd_32 = true },
});
In simd_32
mode, a single wavelet carries two 16-bit values. In simd_64
mode, two wavelets must be ready, otherwise the DSD operation stalls. In
simd_32_or_64
mode, the operation proceeds (i.e. it doesn’t stall) as long
as at least one wavelet is ready.
Reset a Source Operand¶
When the destination operand is a fabric output DSD, once the DSD operation is complete, the architecture can clear the memory vector represented by the source operand of the DSD operation. For instance, the following block of code sets the fabric output DSD properties so the memory represented by the operation’s first source operand is reset to zero when the operation completes.
const out_dsd = @get_dsd(fabout_dsd, .{
.extent = 10,
.fabric_color = out_color,
.zero = .{ .first_source = true },
});
const in_first_dsd = @get_dsd(mem1d_dsd, .{
.tensor_access = |i|{10} -> first_source[i]
});
const in_second_dsd = @get_dsd(mem1d_dsd, .{
.tensor_access = |i|{10} -> second_source[i]
});
// Multiply vectors and send to fabric. Reset `first_source` when complete.
@fmulh(out_dsd, in_first_dsd, out_first_dsd);
To reset the second source operand’s memory, use .zero = .{ .second_source =
true }
. When the DSD operation has just one source operand, use
.second_source = true
. At any time, only one of first_source
or
second_source
can be used.
Advancing Switch Positions¶
Fabric output DSDs can automatically advance switch positions when the last
wavelet is sent. To use this feature, set the advance_switch
field of the
fabric output DSD to be true, like in the example below, which will cause the
switch position for the color out_color
to advance after all ten wavelets
have been sent to the fabric.
const out_dsd = @get_dsd(fabout_dsd, .{
.extent = 10,
.advance_switch = true,
.fabric_color = out_color,
});
Control Wavelet Transform¶
Control Wavelet Transform handles relaying control wavelets. Consider a scenario where there is a “buffering” PE which receives wavelets from the fabric and pushes them into a FIFO, using a microthread. There is also another microthread that pops data from the FIFO and sends them into the fabric. What if there is a requirement to relay control wavelets as well? By default, the approach described above cannot work since the task receives only the “index” and “data” bits of the wavelets, and the bit signifying that a wavelet is a control wavelet is outside of those bits. That means that if a control wavelet is pushed into the FIFO, the control bit is lost, so when it’s the time to pop it, it will be sent away as a regular wavelet, instead of a control wavelet.
To get around this limitation, the control_transform
field can be used. By
specifying control_transform
to be true for the fabric input DSD, when a
control wavelet is received, the two most significant bits of the index portion
of the wavelet are overwritten to signify that the wavelet stored in the FIFO is
a control wavelet. Then, a fabric output DSD with control_transform
set to
true can be used to reconstruct control wavelets and send them to the fabric.
var in_dsd = @get_dsd(fabin_dsd, .{ .fabric_color = recv_channel,
.extent = 100,
.input_queue = @get_input_queue(0),
.control_transform = true });
const out_dsd = @get_dsd(fabout_dsd, .{ .extent = 100,
.fabric_color = send_channel,
.output_queue = @get_output_queue(1),
.control_transform = true });
var buf = @zeros([5]u32);
const fifo = @allocate_fifo(buf);
task buffer() void {
@mov32(fifo, in_dsd, .{ .async = true });
@mov32(out_dsd, fifo, .{ .async = true });
}
Note since the two most significant bits of the index are overwritten, when
control_transform
is used, only the least significant 14 bits of the index
can be utilized by the user. This property can only be used with fabric DSDs.