通过mpi发送mpz_t数组 我使用libgmp(GMP)来处理非常长的整数,存储为 mpz_t :http://gmplib.org/manual/Integer-Internals.html#Integer-Internals mpz_t 变量表示使用符号和幅度的整数,在空间中动态分配和重新分配。 所以我认为 mpz_t 就像指针一样。 如何通过MPI发送带有数据的 mpz_t 变量数组?
函数原型:mpi_limb_t mpihelp_divrem(mpi_ptr_t qp, mpi_size_t qextra_limbs, mpi_ptr_t np, mpi_size_t nsize, mpi_ptr_t dp, mpi_size_t dsize) 返回类型:mpi_limb_t 参数: 类型参数名称 mpi_ptr_t qp mpi_size_t qextra_limbs mpi_ptr_t np mpi_size_t nsize mpi_ptr_t dp...
size_t file_size = fin.tellg(); fin.seekg(0, std::ios::beg); std::cout << "File size: " << file_size << "\n"; char* buf = new char[file_size]; fin.read(buf, file_size); fin.close(); start_send = sc.now(); ...
static inline void mpi_to_mem_block(uint32_t mem_base, const mbedtls_mpi *mpi, size_t hw_words)/* Please see detailed note inside the function body below. * Relevant: https://github.com/espressif/esp-idf/issues/8710 and IDF-6029 ...
integer myid,npc,namelen,re,ierr,ver,subver,m,n,status(MPI_STATUS_SIZE),ipc integer type_block_MPI,type_global_MPI, & blocklens_global(0:ndatatype-1),offsets_global(0:ndatatype-1), & oldtypes_global(0:ndatatype-1), & blocklens_block(0:2),offsets_block(0:...
int ierr, prev, next, tag, rank, size; MPI_Status status; double send_buf[T_SIZE], recv_buf[T_SIZE]; MPI_Init(&argc,&argv); MPI_Comm_rank( MPI_COMM_WORLD, &rank); MPI_Comm_size( MPI_COMM_WORLD, &size); next = rank + 1; ...
classCountDownLatch{public:explicitCountDownLatch(size_tn): mFlyingCount(n) {}voidAdd(size_ti){ mFlyingCount += i; }voidDone(){if(--mFlyingCount ==0) { ch_0.Close(); } }voidWait(){intx; ch_0 >> x; }private: std::atomic<size_t> mFlyingCount {1}; ...
(MPI_COMM_WORLD,&mr);MPI_Comm_size(MPI_COMM_WORLD,&nr);constsize_t dim=1024;constsize_t repeat=100;std::vector<double>send(dim,static_cast<double>(mr)+1.0);std::vector<double>recv(dim,0.0);MPI_Win win;MPI_Win_create(recv.data(),recv.size()*sizeof(double),sizeof(double),MPI_...
ncclResult_tNCCLSendrecv(void*sendbuff,/* 发送的buffer */size_tsendcount,/* 发送的元素数量 */ncclDataType_tdatatype,/* 发送的数据类型 */intpeer,/* 要合作的rank */void*recvbuff,/* 接收buffer */size_trecvcount,/* 接收的数据数量 */ncclComm_tcomm,/* Communicator */cudaStream_tstream...
T paro为并行开销时间,T comm为相互通信时间); 存储器性能(存储器的层次结构(C,L,B),估计存储器的带宽); 并行与通信开销 PowerPC (每个周期15ns执行4flops; 创建一个进程1.4ms可执行372000flops) 开销的测量:乒--乓方法(Ping-Pong Scheme), 节点0发送m个字节给节点1; 节点1从节点0接收m个字节后,立即将...