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z'FromCImportStatNode.declaration_matchesc C s | S )Nr& )r~ rA r& r& r' rp � s z'FromCImportStatNode.analyse_expressionsc C s d S )Nr& )r~ rU r& r& r' r� � s z+FromCImportStatNode.generate_execution_code) rK rk rl r� r� r+ r7 r� r8 rp r� r& r& r& r' r3 � s .r3 c @ s. e Zd ZdgZdZdd� Zdd� Zdd� Zd S )
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#r: c @ s e Zd ZdZdZdS )� ParallelNodez4
Base class for cython.parallel constructs.
N)rK rk rl rx r� r& r& r& r' r? Z s r? c sH e Zd ZdZddgZdZdZdZdZdZ dZ
e j e j
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d� Z dd� Z dd� Z d;dd�Z dd� Z dd� Z!dd� Z"dd � Z#d<d d �Z$d d!� Z%d"d#� Z&d$d%� Z'd&d'� Z(d=d(d)�Z)d*d+� Z*d,d-� Z+d.d/� Z,d0d1� Z-d>d2d3�Z.d4Z/d5Z0d6e/e0f Z1d7d8� Z2d9d:� Z3� Z4S )?�ParallelStatNodea
Base class for 'with cython.parallel.parallel():' and 'for i in prange():'.
assignments { Entry(var) : (var.pos, inplace_operator_or_None) }
assignments to variables in this parallel section
parent parent ParallelStatNode or None
is_parallel indicates whether this node is OpenMP parallel
(true for #pragma omp parallel for and
#pragma omp parallel)
is_parallel is true for:
#pragma omp parallel
#pragma omp parallel for
sections, but NOT for
#pragma omp for
We need this to determine the sharing attributes.
privatization_insertion_point a code insertion point used to make temps
private (esp. the "nsteps" temp)
args tuple the arguments passed to the parallel construct
kwargs DictNode the keyword arguments passed to the parallel
construct (replaced by its compile time value)
r� � num_threadsNFr c s< t t| �j|f|� |�d�p i | _t� | _i | _g | _d S )Nrd ) rd r@ r� r- rd ry �seen_closure_vars�privates�assigned_nodes)r~ r% rs )rJ r& r' r� � s
zParallelStatNode.__init__c
C sJ | j �|� d | _| jr�g }t� }x�| jjD ]~}|jj|krPt| j d|jj � |�
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r� } zt| jj d� W d d }~X Y nX ni | _xB| j�� D ]4\}}|| jk�r4t| j d| � n t| ||� �qW d S )Nz$Duplicate keyword argument found: %srA � chunksizez=Only compile-time values may be supplied as keyword argumentsz Invalid keyword argument: %s)r� r� rA rs ry r6 r� r7 r r% r� r� � is_prangerE r rI � Exceptionrc �valid_keyword_argumentsr� )r~ rA �pairs�seenZdictitemrf r r r& r& r' r� � s4
" z%ParallelStatNode.analyse_declarationsc C s� | j r| j �|�| _ | jr(| j�|�| _| j�|�| _| �|� | j d k r�| jrr| jj d k rr| jjsrt| jd� nJ| jr�| jjs�t| jd� n.| j j j
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� r�| j j jr�| j �tj|��|�| _ | S )Nz-num_threads already declared in outer sectionz;num_threads must be declared in the parent parallel sectionr z.argument to num_threads must be greater than 0)rA rp rE r� �analyse_sharing_attributes�parentrF r r% r/ r� r� rI r r; r r
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z$ParallelStatNode.analyse_expressionsc C sn xh| j �� D ]Z\}\}}| jr<| js<|| jj kr<t|d� q | jsR|rRt|d� q d}| �||||� q W dS )z�
Analyse the privates for this block and set them in self.privates.
This should be called in a post-order fashion during the
analyse_expressions phase
z0Cannot assign to private of outer parallel blockz*Reductions not allowed for parallel blocksTN)rd rc rF � is_parallelrL r �propagate_var_privatization)r~ rA r� r% rY � lastprivater& r& r' rK � s
z+ParallelStatNode.analyse_sharing_attributesc C sl ||f| j |< |jjr$t|d� dS | jrh| jsF|| jjkrF| jj}n| j}|rh|sX|rh|�||||� dS )a
Propagate the sharing attributes of a variable. If the privatization is
determined by a parent scope, done propagate further.
If we are a prange, we propagate our sharing attributes outwards to
other pranges. If we are a prange in parallel block and the parallel
block does not determine the variable private, we propagate to the
parent of the parent. Recursion stops at parallel blocks, as they have
no concept of lastprivate or reduction.
So the following cases propagate:
sum is a reduction for all loops:
for i in prange(n):
for j in prange(n):
for k in prange(n):
sum += i * j * k
sum is a reduction for both loops, local_var is private to the
parallel with block:
for i in prange(n):
with parallel:
local_var = ... # private to the parallel
for j in prange(n):
sum += i * j
Nested with parallel blocks are disallowed, because they wouldn't
allow you to propagate lastprivates or reductions:
#pragma omp parallel for lastprivate(i)
for i in prange(n):
sum = 0
#pragma omp parallel private(j, sum)
with parallel:
#pragma omp parallel
with parallel:
#pragma omp for lastprivate(j) reduction(+:sum)
for j in prange(n):
sum += i
# sum and j are well-defined here
# sum and j are undefined here
# sum and j are undefined here
z9Memoryview slices can only be shared in parallel sectionsN) rC r/ r� r rF rM rL rd rN )r~ r� r% rY rO rL r& r& r' rN s 5
z,ParallelStatNode.propagate_var_privatizationc C s� | j r| j �||�S |j| jkr&|jS |j�|jd�}| j�|j� | j�|� | j� ||jf� |�
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Helper function that allocate a temporary for a closure variable that
is assigned to.
Tz%s = %s;N) rL �_allocate_closure_tempr rB r� r� r/ r� �modified_entriesr rO )r~ rU r� r r& r& r' rP R s z'ParallelStatNode._allocate_closure_tempc C st d}xjt | j�� �D ]X\}\}}|s|r0||kr|j�� }|r|rP|�d� d}|�d|j|j�|�f � qW d S )NTz4/* Initialize private variables to invalid values */Fz%s = %s;)�sortedrC rc r/ �
invalid_valuerO r rE )r~ rU �excluderb r� rY rO rS r& r& r' �initialize_privates_to_nanh s
z+ParallelStatNode.initialize_privates_to_nanc C s0 | j }|jj}||j_|�|� ||j_|�� S )N)�1begin_of_parallel_control_block_point_after_declsr� �ownerrD r� )r~ rU r� r� rW r& r& r' �evaluate_before_blockw s
z&ParallelStatNode.evaluate_before_blockc C s& | j dk r"|�d| �|| j � � dS )zS
Write self.num_threads if set as the num_threads OpenMP directive
Nz num_threads(%s))rA r� rX )r~ rU r& r& r' �put_num_threads� s
z ParallelStatNode.put_num_threadsc C s6 g | _ x*t| j�D ] }|js"|jr| �||� qW dS )a
If a variable is in a scope object, we need to allocate a temp and
assign the value from the temp to the variable in the scope object
after the parallel section. This kind of copying should be done only
in the outermost parallel section.
N)rQ rR rd Z from_closurer� rP )r~ rU r� r& r& r' �declare_closure_privates� s z)ParallelStatNode.declare_closure_privatesc C s@ x:| j D ]0\}}|�d||jf � |j�|j� ||_qW dS )z�
Release any temps used for variables in scope objects. As this is the
outermost parallel block, we don't need to delete the cnames from
self.seen_closure_vars.
z%s = %s;N)rQ rO r r� r� )r~ rU r� r_ r& r& r' �release_closure_privates� s z)ParallelStatNode.release_closure_privatesr& c
C s� | j r�| j}|j�� | _}g g }}x6t|�D ]*\}}|jsD|jrP|�|� q0|�|� q0W |rv|� dd�
|� � |r�|� dd�
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Make any used temporaries private. Before the relevant code block
code.start_collecting_temps() should have been called.
z private(%s)z, z firstprivate(%s)z private(%s, %s, %s)z shared(%s)N)rM � privatization_insertion_pointr� Zstop_collecting_tempsr� rR r; r� r r� r� �breaking_label_usedr � parallel_why�error_label_used�extend� parallel_exc�pos_info)
r~ rU Z
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z ParallelStatNode.privatize_tempsc C sh | j rd| jsd|�d� xLt| j�D ]>\}}|jr@|j|dd� q"|jr"|�||� |�d| � q"W d S )Nz /* Clean up any temporaries */F)r� z
%s = NULL;) rM �is_nested_prangerO rR r� r� r r; r )r~ rU r� r/ r& r& r' �
cleanup_temps� s
z ParallelStatNode.cleanup_tempsc C sT |� � | _|�� | _|j| _|jdd�|_|�� |�� | _ |�� | _
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Sets up a block that surrounds the parallel block to determine
how the parallel section was exited. Any kind of return is
trapped (break, continue, return, exceptions). This is the idea:
{
int why = 0;
#pragma omp parallel
{
return # -> goto new_return_label;
goto end_parallel;
new_return_label:
why = 3;
goto end_parallel;
end_parallel:;
#pragma omp flush(why) # we need to flush for every iteration
}
if (why == 3)
goto old_return_label;
}
�return)r: N) r� r� r� r� r� r� r� r$ r� �%begin_of_parallel_control_block_pointrV �"undef_builtin_expect_apple_gcc_bug)r~ rU r& r& r' �!setup_parallel_control_flow_block� s
z2ParallelStatNode.setup_parallel_control_flow_blockc C s |� � | _dS )a�
Each OpenMP thread in a parallel section that contains a with gil block
must have the thread-state initialized. The call to
PyGILState_Release() then deallocates our threadstate. If we wouldn't
do this, each with gil block would allocate and deallocate one, thereby
losing exception information before it can be saved before leaving the
parallel section.
N)r� �begin_of_parallel_block)r~ rU r& r& r' �begin_parallel_block� s z%ParallelStatNode.begin_parallel_blockc C s� | j r�| j}|}|�d� |jdd� |�d� |�d� |�d� |�d� |�d� |�d� |�� |�d� | �|� |�� |�d � |�d
� |�d� d S ) a�
To ensure all OpenMP threads have thread states, we ensure the GIL
in each thread (which creates a thread state if it doesn't exist),
after which we release the GIL.
On exit, reacquire the GIL and release the thread state.
If compiled without OpenMP support (at the C level), then we still have
to acquire the GIL to decref any object temporaries.
z#ifdef _OPENMPT)r� ZPy_BEGIN_ALLOW_THREADSz#endif /* _OPENMP */ZPy_END_ALLOW_THREADSz#elsez{
z#ifndef _OPENMPz}
N)r_ rj rO r� Zput_safere r� )r~ rU Z
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z#ParallelStatNode.end_parallel_blockc C s^ |� � }|� � }d| _d| _d| _g | _|�� }x.|D ]&}|�|�r6| jpR||jk| _d| _q6W | jrp|�|� x�t |�D ]�\}}|�|�s�qz||jk}|�
|� |r�|s�||j kr�d| _| � |� |�
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Trap any kind of return inside a parallel construct. 'should_flush'
indicates whether the variable should be flushed, which is needed by
prange to skip the loop. It also indicates whether we need to register
a continue (we need this for parallel blocks, but not for prange
loops, as it is a direct jump there).
It uses the same mechanism as try/finally:
1 continue
2 break
3 return
4 error
FTz%s = %d;r z#pragma omp flush(%s)N)r� �any_label_usedr] r_ �parallel_private_tempsr r� r� r� r r r� �fetch_parallel_exceptionrO r r^ rF �save_parallel_varsr� ) r~ rU � should_flushZsave_lastprivates_labelZdont_return_labelZ
all_labelsr� r# Zis_continue_labelr& r& r' �trap_parallel_exit! sF
z#ParallelStatNode.trap_parallel_exitc
C s� d| j }|�d| � t j d7 _ |�� | j}d}x�t| j�� �D ]�\}\}}|rH|jj rbqH|j�
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The following shenanigans are instated when we break, return or
propagate errors from a prange. In this case we cannot rely on
lastprivate() to do its job, as no iterations may have executed yet
in the last thread, leaving the values undefined. It is most likely
that the breaking thread has well-defined values of the lastprivate
variables, so we keep those values.
z __pyx_parallel_lastprivates%dz#pragma omp critical(%s)r r z__pyx_parallel_temp%dz = r� z%s %s%s;z%s = %s;N)�critical_section_counterr� r@ r$ rg rR rC rc r/ r; r> r rS rE rO rn r r% )
r~ rU � section_namer� Z
temp_countr� rY rO Z type_decl�
temp_cname�
private_cnamerS r r& r& r' rp ]! s*
z#ParallelStatNode.save_parallel_varsc C s� |� � |jdd� |�dtj � |�dtj � |�d| j � tt| j | j
�� }d|j _ |�dt
|� � |�tj� |�d� |�� |�� dS ) a^
As each OpenMP thread may raise an exception, we need to fetch that
exception from the threadstate and save it for after the parallel
section where it can be re-raised in the master thread.
Although it would seem that __pyx_filename, __pyx_lineno and
__pyx_clineno are only assigned to under exception conditions (i.e.,
when we have the GIL), and thus should be allowed to be shared without
any race condition, they are in fact subject to the same race
conditions that they were previously when they were global variables
and functions were allowed to release the GIL:
thread A thread B
acquire
set lineno
release
acquire
set lineno
release
acquire
fetch exception
release
skip the fetch
deallocate threadstate deallocate threadstate
T)r� z#pragma omp flush(%s)z
if (!%s) {z'__Pyx_ErrFetchWithState(&%s, &%s, &%s);z%s = %s; %s = %s; %s = %s;r� N)r$ r� r� r �parallel_exc_typerO ra r r; �parallel_pos_inforb r� Zuses_error_indicatorr� r� r� r% )r~ rU rb r& r& r' ro �! s z)ParallelStatNode.fetch_parallel_exceptionc C sh |� � |jdd� |�tj� |�d| j � tt| j | j
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This ends the parallel control flow block and based on how the parallel
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Here break should be trapped in the parallel block, and propagated to
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for i in prange(start, stop, step):
...
becomes
nsteps = (stop - start) / step;
i = start;
#pragma omp parallel for lastprivate(i)
for (temp = 0; temp < nsteps; temp++) {
i = start + step * temp;
...
}
Note that accumulation of 'i' would have a data dependency
between iterations.
Also, you can't do this
for (i = start; i < stop; i += step)
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as the '<' operator should become '>' for descending loops.
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/* Test for GCC > 2.95 */
#if defined(__GNUC__) && (__GNUC__ > 2 || (__GNUC__ == 2 && (__GNUC_MINOR__ > 95)))
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#define unlikely(x) __builtin_expect(!!(x), 0)
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Py_INCREF(type);
Py_INCREF(value);
Py_INCREF(tb);
PyTuple_SET_ITEM(exc_info, 0, type);
PyTuple_SET_ITEM(exc_info, 1, value);
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