comparison DEPENDENCIES/generic/include/boost/graph/parallel/distribution.hpp @ 16:2665513ce2d3

Add boost headers

+// Copyright 2004 The Trustees of Indiana University.
+
+// Use, modification and distribution is subject to the Boost Software
+// License, Version 1.0. (See accompanying file LICENSE_1_0.txt or copy at
+// http://www.boost.org/LICENSE_1_0.txt)
+
+//  Authors: Douglas Gregor
+//           Peter Gottschling
+//           Andrew Lumsdaine
+#ifndef BOOST_PARALLEL_DISTRIBUTION_HPP
+#define BOOST_PARALLEL_DISTRIBUTION_HPP
+
+#ifndef BOOST_GRAPH_USE_MPI
+#error "Parallel BGL files should not be included unless <boost/graph/use_mpi.hpp> has been included"
+#endif
+
+#include <cstddef>
+#include <vector>
+#include <algorithm>
+#include <numeric>
+#include <boost/assert.hpp>
+#include <boost/iterator/counting_iterator.hpp>
+#include <boost/random/uniform_int.hpp>
+#include <boost/shared_ptr.hpp>
+#include <typeinfo>
+
+namespace boost { namespace parallel {
+
+template<typename ProcessGroup, typename SizeType = std::size_t>
+class variant_distribution
+{
+public:
+  typedef typename ProcessGroup::process_id_type process_id_type;
+  typedef typename ProcessGroup::process_size_type process_size_type;
+  typedef SizeType size_type;
+
+private:
+  struct basic_distribution
+  {
+    virtual ~basic_distribution() {}
+    virtual size_type block_size(process_id_type, size_type) const = 0;
+    virtual process_id_type in_process(size_type) const = 0;
+    virtual size_type local(size_type) const = 0;
+    virtual size_type global(size_type) const = 0;
+    virtual size_type global(process_id_type, size_type) const = 0;
+    virtual void* address() = 0;
+    virtual const void* address() const = 0;
+    virtual const std::type_info& type() const = 0;
+  };
+
+  template<typename Distribution>
+  struct poly_distribution : public basic_distribution
+  {
+    explicit poly_distribution(const Distribution& distribution)
+      : distribution_(distribution) { }
+
+    virtual size_type block_size(process_id_type id, size_type n) const
+    { return distribution_.block_size(id, n); }
+
+    virtual process_id_type in_process(size_type i) const
+    { return distribution_(i); }
+
+    virtual size_type local(size_type i) const
+    { return distribution_.local(i); }
+
+    virtual size_type global(size_type n) const
+    { return distribution_.global(n); }
+
+    virtual size_type global(process_id_type id, size_type n) const
+    { return distribution_.global(id, n); }
+
+    virtual void* address() { return &distribution_; }
+    virtual const void* address() const { return &distribution_; }
+    virtual const std::type_info& type() const { return typeid(Distribution); }
+
+  private:
+    Distribution distribution_;
+  };
+
+public:
+  variant_distribution() { }
+
+  template<typename Distribution>
+  variant_distribution(const Distribution& distribution)
+    : distribution_(new poly_distribution<Distribution>(distribution)) { }
+
+  size_type block_size(process_id_type id, size_type n) const
+  { return distribution_->block_size(id, n); }
+  
+  process_id_type operator()(size_type i) const
+  { return distribution_->in_process(i); }
+  
+  size_type local(size_type i) const
+  { return distribution_->local(i); }
+  
+  size_type global(size_type n) const
+  { return distribution_->global(n); }
+
+  size_type global(process_id_type id, size_type n) const
+  { return distribution_->global(id, n); }
+
+  operator bool() const { return distribution_; }
+
+  void clear() { distribution_.reset(); }
+
+  template<typename T>
+  T* as()
+  {
+    if (distribution_->type() == typeid(T))
+      return static_cast<T*>(distribution_->address());
+    else
+      return 0;
+  }
+
+  template<typename T>
+  const T* as() const
+  {
+    if (distribution_->type() == typeid(T))
+      return static_cast<T*>(distribution_->address());
+    else
+      return 0;
+  }
+
+private:
+  shared_ptr<basic_distribution> distribution_;
+};
+
+struct block
+{
+  template<typename LinearProcessGroup>
+  explicit block(const LinearProcessGroup& pg, std::size_t n) 
+    : id(process_id(pg)), p(num_processes(pg)), n(n) { }
+
+  // If there are n elements in the distributed data structure, returns the number of elements stored locally.
+  template<typename SizeType>
+  SizeType block_size(SizeType n) const
+  { return (n / p) + ((std::size_t)(n % p) > id? 1 : 0); }
+
+  // If there are n elements in the distributed data structure, returns the number of elements stored on processor ID
+  template<typename SizeType, typename ProcessID>
+  SizeType block_size(ProcessID id, SizeType n) const
+  { return (n / p) + ((ProcessID)(n % p) > id? 1 : 0); }
+
+  // Returns the processor on which element with global index i is stored
+  template<typename SizeType>
+  SizeType operator()(SizeType i) const
+  { 
+    SizeType cutoff_processor = n % p;
+    SizeType cutoff = cutoff_processor * (n / p + 1);
+
+    if (i < cutoff) return i / (n / p + 1);
+    else return cutoff_processor + (i - cutoff) / (n / p);
+  }
+
+  // Find the starting index for processor with the given id
+  template<typename ID>
+  std::size_t start(ID id) const
+  {
+    std::size_t estimate = id * (n / p + 1);
+    ID cutoff_processor = n % p;
+    if (id < cutoff_processor) return estimate;
+    else return estimate - (id - cutoff_processor);
+  }
+
+  // Find the local index for the ith global element
+  template<typename SizeType>
+  SizeType local(SizeType i) const
+  { 
+    SizeType owner = (*this)(i);
+    return i - start(owner);
+  }
+
+  // Returns the global index of local element i
+  template<typename SizeType>
+  SizeType global(SizeType i) const
+  { return global(id, i); }
+
+  // Returns the global index of the ith local element on processor id
+  template<typename ProcessID, typename SizeType>
+  SizeType global(ProcessID id, SizeType i) const
+  { return i + start(id); }
+
+ private:
+  std::size_t id; //< The ID number of this processor
+  std::size_t p;  //< The number of processors
+  std::size_t n;  //< The size of the problem space
+};
+
+// Block distribution with arbitrary block sizes
+struct uneven_block
+{
+  typedef std::vector<std::size_t>    size_vector;
+
+  template<typename LinearProcessGroup>
+  explicit uneven_block(const LinearProcessGroup& pg, const std::vector<std::size_t>& local_sizes) 
+    : id(process_id(pg)), p(num_processes(pg)), local_sizes(local_sizes)
+  { 
+    BOOST_ASSERT(local_sizes.size() == p);
+    local_starts.resize(p + 1);
+    local_starts[0] = 0;
+    std::partial_sum(local_sizes.begin(), local_sizes.end(), &local_starts[1]);
+    n = local_starts[p];
+  }
+
+  // To do maybe: enter local size in each process and gather in constructor (much handier)
+  // template<typename LinearProcessGroup>
+  // explicit uneven_block(const LinearProcessGroup& pg, std::size_t my_local_size) 
+
+  // If there are n elements in the distributed data structure, returns the number of elements stored locally.
+  template<typename SizeType>
+  SizeType block_size(SizeType) const
+  { return local_sizes[id]; }
+
+  // If there are n elements in the distributed data structure, returns the number of elements stored on processor ID
+  template<typename SizeType, typename ProcessID>
+  SizeType block_size(ProcessID id, SizeType) const
+  { return local_sizes[id]; }
+
+  // Returns the processor on which element with global index i is stored
+  template<typename SizeType>
+  SizeType operator()(SizeType i) const
+  {
+    BOOST_ASSERT (i >= (SizeType) 0 && i < (SizeType) n); // check for valid range
+    size_vector::const_iterator lb = std::lower_bound(local_starts.begin(), local_starts.end(), (std::size_t) i);
+    return ((SizeType)(*lb) == i ? lb : --lb) - local_starts.begin();
+  }
+
+  // Find the starting index for processor with the given id
+  template<typename ID>
+  std::size_t start(ID id) const 
+  {
+    return local_starts[id];
+  }
+
+  // Find the local index for the ith global element
+  template<typename SizeType>
+  SizeType local(SizeType i) const
+  { 
+    SizeType owner = (*this)(i);
+    return i - start(owner);
+  }
+
+  // Returns the global index of local element i
+  template<typename SizeType>
+  SizeType global(SizeType i) const
+  { return global(id, i); }
+
+  // Returns the global index of the ith local element on processor id
+  template<typename ProcessID, typename SizeType>
+  SizeType global(ProcessID id, SizeType i) const
+  { return i + start(id); }
+
+ private:
+  std::size_t              id;           //< The ID number of this processor
+  std::size_t              p;            //< The number of processors
+  std::size_t              n;            //< The size of the problem space
+  std::vector<std::size_t> local_sizes;  //< The sizes of all blocks
+  std::vector<std::size_t> local_starts; //< Lowest global index of each block
+};
+
+
+struct oned_block_cyclic
+{
+  template<typename LinearProcessGroup>
+  explicit oned_block_cyclic(const LinearProcessGroup& pg, std::size_t size)
+    : id(process_id(pg)), p(num_processes(pg)), size(size) { }
+      
+  template<typename SizeType>
+  SizeType block_size(SizeType n) const
+  { 
+    return block_size(id, n);
+  }
+
+  template<typename SizeType, typename ProcessID>
+  SizeType block_size(ProcessID id, SizeType n) const
+  {
+    SizeType all_blocks = n / size;
+    SizeType extra_elements = n % size;
+    SizeType everyone_gets = all_blocks / p;
+    SizeType extra_blocks = all_blocks % p;
+    SizeType my_blocks = everyone_gets + (p < extra_blocks? 1 : 0);
+    SizeType my_elements = my_blocks * size 
+                         + (p == extra_blocks? extra_elements : 0);
+    return my_elements;
+  }
+
+  template<typename SizeType>
+  SizeType operator()(SizeType i) const
+  { 
+    return (i / size) % p;
+  }
+
+  template<typename SizeType>
+  SizeType local(SizeType i) const
+  { 
+    return ((i / size) / p) * size + i % size;
+  }
+
+  template<typename SizeType>
+  SizeType global(SizeType i) const
+  { return global(id, i); }
+
+  template<typename ProcessID, typename SizeType>
+  SizeType global(ProcessID id, SizeType i) const
+  { 
+    return ((i / size) * p + id) * size + i % size;
+  }
+
+ private:
+  std::size_t id;                   //< The ID number of this processor
+  std::size_t p;                    //< The number of processors
+  std::size_t size;                 //< Block size
+};
+
+struct twod_block_cyclic
+{
+  template<typename LinearProcessGroup>
+  explicit twod_block_cyclic(const LinearProcessGroup& pg,
+                             std::size_t block_rows, std::size_t block_columns,
+                             std::size_t data_columns_per_row)
+    : id(process_id(pg)), p(num_processes(pg)), 
+      block_rows(block_rows), block_columns(block_columns), 
+      data_columns_per_row(data_columns_per_row)
+  { }
+      
+  template<typename SizeType>
+  SizeType block_size(SizeType n) const
+  { 
+    return block_size(id, n);
+  }
+
+  template<typename SizeType, typename ProcessID>
+  SizeType block_size(ProcessID id, SizeType n) const
+  {
+    // TBD: This is really lame :)
+    int result = -1;
+    while (n > 0) {
+      --n;
+      if ((*this)(n) == id && (int)local(n) > result) result = local(n);
+    }
+    ++result;
+
+    //    std::cerr << "Block size of id " << id << " is " << result << std::endl;
+    return result;
+  }
+
+  template<typename SizeType>
+  SizeType operator()(SizeType i) const
+  { 
+    SizeType result = get_block_num(i) % p;
+    //    std::cerr << "Item " << i << " goes on processor " << result << std::endl;
+    return result;
+  }
+
+  template<typename SizeType>
+  SizeType local(SizeType i) const
+  { 
+    // Compute the start of the block
+    std::size_t block_num = get_block_num(i);
+    //    std::cerr << "Item " << i << " is in block #" << block_num << std::endl;
+
+    std::size_t local_block_num = block_num / p;
+    std::size_t block_start = local_block_num * block_rows * block_columns;
+
+    // Compute the offset into the block 
+    std::size_t data_row = i / data_columns_per_row;
+    std::size_t data_col = i % data_columns_per_row;
+    std::size_t block_offset = (data_row % block_rows) * block_columns 
+                             + (data_col % block_columns);    
+
+    //    std::cerr << "Item " << i << " maps to local index " << block_start+block_offset << std::endl;
+    return block_start + block_offset;
+  }
+
+  template<typename SizeType>
+  SizeType global(SizeType i) const
+  { 
+    // Compute the (global) block in which this element resides
+    SizeType local_block_num = i / (block_rows * block_columns);
+    SizeType block_offset = i % (block_rows * block_columns);
+    SizeType block_num = local_block_num * p + id;
+
+    // Compute the position of the start of the block (globally)
+    SizeType block_start = block_num * block_rows * block_columns;
+
+    std::cerr << "Block " << block_num << " starts at index " << block_start
+              << std::endl;
+
+    // Compute the row and column of this block
+    SizeType block_row = block_num / (data_columns_per_row / block_columns);
+    SizeType block_col = block_num % (data_columns_per_row / block_columns);
+
+    SizeType row_in_block = block_offset / block_columns;
+    SizeType col_in_block = block_offset % block_columns;
+
+    std::cerr << "Local index " << i << " is in block at row " << block_row
+              << ", column " << block_col << ", in-block row " << row_in_block
+              << ", in-block col " << col_in_block << std::endl;
+
+    SizeType result = block_row * block_rows + block_col * block_columns
+                    + row_in_block * block_rows + col_in_block;
+
+
+    std::cerr << "global(" << i << "@" << id << ") = " << result 
+              << " =? " << local(result) << std::endl;
+    BOOST_ASSERT(i == local(result));
+    return result;
+  }
+
+ private:
+  template<typename SizeType>
+  std::size_t get_block_num(SizeType i) const
+  {
+    std::size_t data_row = i / data_columns_per_row;
+    std::size_t data_col = i % data_columns_per_row;
+    std::size_t block_row = data_row / block_rows;
+    std::size_t block_col = data_col / block_columns;
+    std::size_t blocks_in_row = data_columns_per_row / block_columns;
+    std::size_t block_num = block_col * blocks_in_row + block_row;
+    return block_num;
+  }
+
+  std::size_t id;                   //< The ID number of this processor
+  std::size_t p;                    //< The number of processors
+  std::size_t block_rows;           //< The # of rows in each block
+  std::size_t block_columns;        //< The # of columns in each block
+  std::size_t data_columns_per_row; //< The # of columns per row of data
+};
+
+class twod_random
+{
+  template<typename RandomNumberGen>
+  struct random_int
+  {
+    explicit random_int(RandomNumberGen& gen) : gen(gen) { }
+
+    template<typename T>
+    T operator()(T n) const
+    {
+      uniform_int<T> distrib(0, n-1);
+      return distrib(gen);
+    }
+
+  private:
+    RandomNumberGen& gen;
+  };
+  
+ public:
+  template<typename LinearProcessGroup, typename RandomNumberGen>
+  explicit twod_random(const LinearProcessGroup& pg,
+                       std::size_t block_rows, std::size_t block_columns,
+                       std::size_t data_columns_per_row,
+                       std::size_t n,
+                       RandomNumberGen& gen)
+    : id(process_id(pg)), p(num_processes(pg)), 
+      block_rows(block_rows), block_columns(block_columns), 
+      data_columns_per_row(data_columns_per_row),
+      global_to_local(n / (block_rows * block_columns))
+  { 
+    std::copy(make_counting_iterator(std::size_t(0)),
+              make_counting_iterator(global_to_local.size()),
+              global_to_local.begin());
+
+    random_int<RandomNumberGen> rand(gen);
+    std::random_shuffle(global_to_local.begin(), global_to_local.end(), rand);
+  }
+      
+  template<typename SizeType>
+  SizeType block_size(SizeType n) const
+  { 
+    return block_size(id, n);
+  }
+
+  template<typename SizeType, typename ProcessID>
+  SizeType block_size(ProcessID id, SizeType n) const
+  {
+    // TBD: This is really lame :)
+    int result = -1;
+    while (n > 0) {
+      --n;
+      if ((*this)(n) == id && (int)local(n) > result) result = local(n);
+    }
+    ++result;
+
+    //    std::cerr << "Block size of id " << id << " is " << result << std::endl;
+    return result;
+  }
+
+  template<typename SizeType>
+  SizeType operator()(SizeType i) const
+  { 
+    SizeType result = get_block_num(i) % p;
+    //    std::cerr << "Item " << i << " goes on processor " << result << std::endl;
+    return result;
+  }
+
+  template<typename SizeType>
+  SizeType local(SizeType i) const
+  { 
+    // Compute the start of the block
+    std::size_t block_num = get_block_num(i);
+    //    std::cerr << "Item " << i << " is in block #" << block_num << std::endl;
+
+    std::size_t local_block_num = block_num / p;
+    std::size_t block_start = local_block_num * block_rows * block_columns;
+
+    // Compute the offset into the block 
+    std::size_t data_row = i / data_columns_per_row;
+    std::size_t data_col = i % data_columns_per_row;
+    std::size_t block_offset = (data_row % block_rows) * block_columns 
+                             + (data_col % block_columns);    
+
+    //    std::cerr << "Item " << i << " maps to local index " << block_start+block_offset << std::endl;
+    return block_start + block_offset;
+  }
+
+ private:
+  template<typename SizeType>
+  std::size_t get_block_num(SizeType i) const
+  {
+    std::size_t data_row = i / data_columns_per_row;
+    std::size_t data_col = i % data_columns_per_row;
+    std::size_t block_row = data_row / block_rows;
+    std::size_t block_col = data_col / block_columns;
+    std::size_t blocks_in_row = data_columns_per_row / block_columns;
+    std::size_t block_num = block_col * blocks_in_row + block_row;
+    return global_to_local[block_num];
+  }
+
+  std::size_t id;                   //< The ID number of this processor
+  std::size_t p;                    //< The number of processors
+  std::size_t block_rows;           //< The # of rows in each block
+  std::size_t block_columns;        //< The # of columns in each block
+  std::size_t data_columns_per_row; //< The # of columns per row of data
+  std::vector<std::size_t> global_to_local;
+};
+
+class random_distribution
+{
+  template<typename RandomNumberGen>
+  struct random_int
+  {
+    explicit random_int(RandomNumberGen& gen) : gen(gen) { }
+
+    template<typename T>
+    T operator()(T n) const
+    {
+      uniform_int<T> distrib(0, n-1);
+      return distrib(gen);
+    }
+
+  private:
+    RandomNumberGen& gen;
+  };
+  
+ public:
+  template<typename LinearProcessGroup, typename RandomNumberGen>
+  random_distribution(const LinearProcessGroup& pg, RandomNumberGen& gen,
+                      std::size_t n)
+    : base(pg, n), local_to_global(n), global_to_local(n)
+  {
+    std::copy(make_counting_iterator(std::size_t(0)),
+              make_counting_iterator(n),
+              local_to_global.begin());
+
+    random_int<RandomNumberGen> rand(gen);
+    std::random_shuffle(local_to_global.begin(), local_to_global.end(), rand);
+                        
+
+    for (std::vector<std::size_t>::size_type i = 0; i < n; ++i)
+      global_to_local[local_to_global[i]] = i;
+  }
+
+  template<typename SizeType>
+  SizeType block_size(SizeType n) const
+  { return base.block_size(n); }
+
+  template<typename SizeType, typename ProcessID>
+  SizeType block_size(ProcessID id, SizeType n) const
+  { return base.block_size(id, n); }
+
+  template<typename SizeType>
+  SizeType operator()(SizeType i) const
+  {
+    return base(global_to_local[i]);
+  }
+
+  template<typename SizeType>
+  SizeType local(SizeType i) const
+  { 
+    return base.local(global_to_local[i]);
+  }
+
+  template<typename ProcessID, typename SizeType>
+  SizeType global(ProcessID p, SizeType i) const
+  { 
+    return local_to_global[base.global(p, i)];
+  }
+
+  template<typename SizeType>
+  SizeType global(SizeType i) const
+  { 
+    return local_to_global[base.global(i)];
+  }
+
+ private:
+  block base;
+  std::vector<std::size_t> local_to_global;
+  std::vector<std::size_t> global_to_local;
+};
+
+} } // end namespace boost::parallel
+
+#endif // BOOST_PARALLEL_DISTRIBUTION_HPP
+