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254 lines
11 KiB
Matlab
254 lines
11 KiB
Matlab
% wrapper class around sharedmatrix function , it tries to go around so bugs and
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% crashes of the code and safely use it for fast interprocess sharing of
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% data
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% Use:
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% self = shm(protected = false, shm_key = randi(1e9))
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%
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% COMPILE: mex -R2017b @shm/private/sharedmatrix.c -output @shm/private/sharedmatrix
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% CLEAN all allocated memory :
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% !ipcs -m | cut -d' ' -f2 | grep '^[0-9]' | while read x; do ipcrm -m $x; done
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%
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% % EXAMPLE:
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% x = randn(10,'single')+1i;
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% s = shm();
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% s.upload(x)
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% s.detach; % locally forget the data
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% [s, data] = s.attach % load them back from shared memory
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% disp(s) % show the SHM class
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% disp(data)
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% clear s % or s.detach
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% disp(data-x)
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%*-----------------------------------------------------------------------*
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%| |
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%| Except where otherwise noted, this work is licensed under a |
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%| Creative Commons Attribution-NonCommercial-ShareAlike 4.0 |
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%| International (CC BY-NC-SA 4.0) license. |
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%| |
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%| Copyright (c) 2018 by Paul Scherrer Institute (http://www.psi.ch) |
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%| |
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%| Author: CXS group, PSI |
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%*-----------------------------------------------------------------------*
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% You may use this code with the following provisions:
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%
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% If the code is fully or partially redistributed, or rewritten in another
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% computing language this notice should be included in the redistribution.
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%
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% If this code, or subfunctions or parts of it, is used for research in a
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% publication or if it is fully or partially rewritten for another
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% computing language the authors and institution should be acknowledged
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% in written form in the publication: “Data processing was carried out
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% using the “cSAXS matlab package” developed by the CXS group,
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% Paul Scherrer Institut, Switzerland.”
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% Variations on the latter text can be incorporated upon discussion with
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% the CXS group if needed to more specifically reflect the use of the package
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% for the published work.
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%
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% A publication that focuses on describing features, or parameters, that
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% are already existing in the code should be first discussed with the
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% authors.
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%
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% This code and subroutines are part of a continuous development, they
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% are provided “as they are” without guarantees or liability on part
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% of PSI or the authors. It is the user responsibility to ensure its
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% proper use and the correctness of the results.
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classdef shm < handle
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properties (GetAccess = 'public', SetAccess = 'private')
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shm_key;
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end
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properties (GetAccess = 'public', SetAccess = 'public')
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protected; % dont delete shared variable when cleared
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data_handle;
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end
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properties (GetAccess = 'private', SetAccess = 'private')
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isComplex;
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end
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%% METHODS:
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methods ( Access = 'public' )
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function self = shm(varargin)
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% generate a key for the shared memory, use random number to
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% avoid collisions between several processes
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if nargin < 2
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self.shm_key = randi(1e9);
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else
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self.shm_key = varargin{2};
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end
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self.isComplex = false;
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% make sure that @shm is under all curcumstancess seen by
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% matlab, otherwise the share memory may result in matlab crash
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fpath = mfilename('fullpath');
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fpath = fpath(1:end-8);
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if ~contains(path, fpath)
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addpath(fpath);
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end
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if nargin < 1
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self.protected = false;
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else
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self.protected = varargin{1};
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end
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end
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function disp(self)
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if self.isattached()
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fprintf(['Size of stored data : %i', repmat('x%i',1,ndims(self.data_handle{1})-1),'\n'], size(self.data_handle{1}))
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fprintf('Class of stored data: %s \n', class(self.data_handle{1}))
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else
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disp('No attached data')
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end
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fprintf('Protected: %i \n', self.protected)
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fprintf('Complex: %i \n', self.isComplex)
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!ipcs -m
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% clear all allocated memory
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% !ipcs -m | cut -d' ' -f2 | grep '^[0-9]' | while read x; do ipcrm -m $x; done
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end
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function upload(self, data)
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% only create the memory space and upload there the data
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% if isnumeric(data)
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assert(isnumeric(data) || islogical(data), 'Only numeric arrays are tested to work safely')
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assert(~isa(data, 'double') || isscalar(data), 'Use single precision to make it fast/memory effecient')
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assert(numel(data)*4 < 100e9, 'Datasets than 100GB may result in failure, TESTME')
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% gather the data from GPU
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if isa(data, 'gpuArray')
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data = gather(data);
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end
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if isscalar(data) && isa(data, 'double')
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data = single(data);
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end
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% end
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self.free_safe(); % clear the memory if it was used
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self.create_shm(data, true); % upload to storage
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end
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function allocate(self, data)
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% only create the memory space, do not write any data
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assert(isnumeric(data), 'Only numeric arrays are tested to work safely')
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assert(~isa(data, 'double') , 'Use single/integer precision to make it fast/memory effecient')
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assert(numel(data)*4 < 100e9, 'Datasets than 100GB may result in failure, TESTME')
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self.free_safe(); % clear the memory if it was used
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self.create_shm(data, false); % use only the array to allocate the storage
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end
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function [self, data] = attach(self)
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assert(nargout < 3 && nargout > 0, 'Number of output argument has to be 1 or 2')
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if ~self.isattached()
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try
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self.data_handle=sharedmatrix('attach',self.shm_key);
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catch err
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if strcmpi(err.identifier,'MATLAB:sharedmatrix:attach')
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error('No shared data available at address: %i', self.shm_key)
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end
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rethrow(err)
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end
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end
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if ~isempty(self.data_handle{2})
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%% very bad option because memcpy is enforced, but the only solution till sharedmatrix.c is properly fixed
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data = complex(self.data_handle{:});
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else
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data = self.data_handle{1};
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end
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end
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function detach(self)
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if self.isattached()
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try
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sharedmatrix('detach',self.shm_key,self.data_handle);
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catch err
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warning(err.message)
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end
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self.data_handle = [];
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end
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end
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function free(self)
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% detach the shared memory
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self.detach();
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% and immediatelly delete the memory to avoid pilling it up
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try sharedmatrix('free',self.shm_key); end
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end
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end
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methods ( Access = 'private' )
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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%%%%%%%%%%%%% use MEX file %%%%%%%%%%%%%%%
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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varargout = sharedmatrix(varargin)
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%%%%%%%% other auxiliary functions %%%%%%
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function shmsiz = create_shm(self, data, clone)
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if nargin < 3
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clone = false; % clone == false -> only create the memory space, do not write any data
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end
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if isnumeric(data) && ~isreal(data)
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%warning('SHM:complex_numbers', 'the sharematrix.c code was modified for matlab newer than R2018b, resulting in very poor performance in complex-valued operations')
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%warning('off', 'SHM:complex_numbers');
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data_handle = {real(data), imag(data)};
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else
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data_handle = {data, []};
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end
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try
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shmsiz=sharedmatrix('clone',self.shm_key,data_handle, ~clone);
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catch err
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if strcmpi(err.identifier, 'MATLAB:mex:ErrInvalidMEXFile')
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% recompile the MEX file
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mex @shm/private/sharedmatrix.c -output @shm/private/sharedmatrix
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shmsiz=sharedmatrix('clone',self.shm_key,data_handle, ~clone);
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else
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disp(err)
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shmsiz = 0;
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end
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end
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if shmsiz < numel(data)*class2byte(data)
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% it was not possible to allocate enough memory for data
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self.free_safe();
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disp('Availiable memory:')
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! free -h
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fprintf('Required memory: %3.2fGB \n', numel(data)*class2byte(data)/1e9)
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! ipcs -m
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disp(' Use following command to clean all allocated memory ')
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disp('! ipcs -m | cut -d'' '' -f2 | grep ''^[0-9]'' | while read x; do ipcrm -m $x; done')
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error('Shared memory allocation failed, maybe free memory was too low')
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end
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self.isComplex = ~isreal(data);
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end
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function status = isattached(self)
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% return true is the data are attached
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status = ~(isempty(self.data_handle) || (iscell(self.data_handle) && isempty(self.data_handle{1})));
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end
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function delete(self)
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self.free_safe();
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end
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function free_safe(self)
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% detach the shared memory
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self.detach();
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if ~self.protected
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% and immediatelly delete the memory to avoid pilling it up
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try sharedmatrix('free',self.shm_key); end
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%try sharedmatrix('free',self.shm_key+1); end
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end
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end
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end
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end
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function out = class2byte(in)
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numclass = {'double'; 'single'; 'int8'; 'int16'; 'int32'; 'int64'; 'uint8'; 'uint16'; 'uint32'; 'uint64'};
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numbytes = [NaN;8;4;1;2;4;8;1;2;4;8];
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[~,loc] = ismember(class(in),numclass);
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out = numbytes(loc+1);
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if ~isreal(in)
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out = out * 2;
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end
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end
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