Introduction

The previous section discussed minimizing data transfers between host and device. This section discusses ways to speed up data transfers when there is a need to move data between host and device.

When moving data repeatedly between host and device, the data transfer rate is maximized when both the source and destination are in Unified Shared Memory (USM).

In this section, we show how performance can be improved by calling SYCL and OpenMP APIs to use host Unified Shared Memory (USM), instead of system memory (such as memory allocated using malloc or new).

Optimizing Data Transfers in SYCL

In SYCL, data transfers between host and device may be explicit via the use of the SYCL memcpy function, or implicit via the use of SYCL buffers and accessors.

Case 1: Data transfers using buffers

In the case of SYCL buffers constructed with a pointer to pre-allocated system memory, the SYCL runtime has the capability to use host USM at buffer creation, and to release the host USM at buffer destruction. To enable this capability, a buffer has to be created with a host pointer, for example:

int* hostptr = (int*)malloc(4*sizeof(int));
buffer<int, 1> Buffer(hostptr,4);

and then the environment variable SYCL_USM_HOSTPTR_IMPORT=1 should be set at runtime.

Case 2: Data transfers using SYCL data movement APIs

When the host data allocation is under user control, and the allocated pointer is going to be used in a data transfer API, the user may use USM functions such as malloc_host to allocate host USM memory instead of system memory.

If the source code where memory is allocated is not available or cannot be modified then, for efficient data transfers, system memory can be imported (prepared for device copy) before the first data transfer, and released after all uses and data transfers are completed.

A set of APIs are provided for import (prepare) and release. They give the programmer explicit control over the address range and the duration of the import.

SYCL Experimental Prepare and Release APIs

The interfaces for the SYCL prepare and release APIs are as follows:

void* sycl::prepare_for_device_copy
      (void* ptr, size_t numBytes, sycl::context& syclContext)

void* sycl::prepare_for_device_copy
      (void* ptr, size_t numBytes, sycl::queue& syclQueue)

void sycl::release_from_device_copy
     (void* ptr, sycl::context& syclContext)

void sycl::release_from_device_copy
     (void* ptr, sycl::queue& syclQueue)

See sycl_ext_oneapi_copy_optimize for a description of the APIs.

The APIs are simple to use, but the onus is on the user to ensure correctness and safety with respect to the lifetime of the memory ranges.

Notes:

• If the numBytes argument is not the same as the size of the malloc’ed memory block (for example, if the malloc’ed memory is 1024 bytes, but numBytes is 512 or 2048), the guidance here would be to use a size for the import (prepare) that matches the data transfer size. If the true allocation is bigger, then importing less than the true allocation has no ill effects. Importing more than the true allocation is a user error.

• The prepare/release APIs are experimental and are subject to change.

SYCL Example

The following example, sycl_prepare_bench.cpp, measures the rate of data transfer between host and device. The data transfer size can be varied. The program prints device-to-host and host-to-device data transfer rate, measured in Gigabytes per second. Switches passed to the program are used to control data transfer direction, whether or not the SYCL prepare API is used, and a range of transfer sizes. The switches are listed in the example source.

In the program, the import (prepare) is done once at the beginning, and the release is done once at the end, using the following calls:

sycl::ext::oneapi::experimental::prepare_for_device_copy(
    hostp, transfer_upper_limit, dq);

sycl::ext::oneapi::experimental::release_from_device_copy(hostp, dq);

In between the above calls, there is a loop that repeatedly does memcpy involving the pointer hostp.

#include <math.h>
#include <stdlib.h>
#include <chrono>
#include <time.h>
#include <unistd.h>
#include <sycl/sycl.hpp>

using namespace sycl;

static const char *usage_str =
    "\n ze_bandwidth [OPTIONS]"
    "\n"
    "\n OPTIONS:"
    "\n  -t, string               selectively run a particular test:"
    "\n      h2d or H2D                       run only Host-to-Device tests"
    "\n      d2h or D2H                       run only Device-to-Host tests "
    "\n                            [default:  both]"
    "\n  -q                       minimal output"
    "\n                            [default:  disabled]"
    "\n  -v                       enable verificaton"
    "\n                            [default:  disabled]"
    "\n  -i                       set number of iterations per transfer"
    "\n                            [default:  500]"
    "\n  -s                       select only one transfer size (bytes) "
    "\n  -sb                      select beginning transfer size (bytes)"
    "\n                            [default:  1]"
    "\n  -se                      select ending transfer size (bytes)"
    "\n                            [default: 2^28]"
    "\n  -l                       use SYCL prepare_for_device_copy/release_from_device_copy APIs"
    "\n                            [default: disabled]"
    "\n  -h, --help               display help message"
    "\n";

static uint32_t sanitize_ulong(char *in) {
  unsigned long temp = strtoul(in, NULL, 0);
  if (ERANGE == errno) {
    fprintf(stderr, "%s out of range of type ulong\n", in);
  } else if (temp > UINT32_MAX) {
    fprintf(stderr, "%ld greater than UINT32_MAX\n", temp);
  } else {
    return static_cast<uint32_t>(temp);
  }
  return 0;
}

size_t transfer_lower_limit = 1;
size_t transfer_upper_limit = (1 << 28);
bool verify = false;
bool run_host2dev = true;
bool run_dev2host = true;
bool verbose = true;
bool prepare = false;
uint32_t ntimes = 500;

//  kernel latency
int main(int argc, char **argv) {
  for (int i = 1; i < argc; i++) {
    if ((strcmp(argv[i], "-h") == 0) || (strcmp(argv[i], "--help") == 0)) {
      std::cout << usage_str;
      exit(0);
    } else if (strcmp(argv[i], "-q") == 0) {
      verbose = false;
    } else if (strcmp(argv[i], "-v") == 0) {
      verify = true;
    } else if (strcmp(argv[i], "-l") == 0) {
      prepare = true;
    } else if (strcmp(argv[i], "-i") == 0) {
      if ((i + 1) < argc) {
        ntimes = sanitize_ulong(argv[i + 1]);
        i++;
      }
    } else if (strcmp(argv[i], "-s") == 0) {
      if ((i + 1) < argc) {
        transfer_lower_limit = sanitize_ulong(argv[i + 1]);
        transfer_upper_limit = transfer_lower_limit;
        i++;
      }
    } else if (strcmp(argv[i], "-sb") == 0) {
      if ((i + 1) < argc) {
        transfer_lower_limit = sanitize_ulong(argv[i + 1]);
        i++;
      }
    } else if (strcmp(argv[i], "-se") == 0) {
      if ((i + 1) < argc) {
        transfer_upper_limit = sanitize_ulong(argv[i + 1]);
        i++;
      }
    } else if ((strcmp(argv[i], "-t") == 0)) {
      run_host2dev = false;
      run_dev2host = false;

      if ((i + 1) >= argc) {
        std::cout << usage_str;
        exit(-1);
      }
      if ((strcmp(argv[i + 1], "h2d") == 0) ||
          (strcmp(argv[i + 1], "H2D") == 0)) {
        run_host2dev = true;
        i++;
      } else if ((strcmp(argv[i + 1], "d2h") == 0) ||
                 (strcmp(argv[i + 1], "D2H") == 0)) {
        run_dev2host = true;
        i++;
      } else {
        std::cout << usage_str;
        exit(-1);
      }
    } else {
      std::cout << usage_str;
      exit(-1);
    }
  }

  queue dq;
  device dev = dq.get_device();
  size_t max_compute_units = dev.get_info<info::device::max_compute_units>();
  auto BE = dq.get_device()
                    .template get_info<sycl::info::device::opencl_c_version>()
                    .empty()
                ? "L0"
                : "OpenCL";
  if (verbose)
    std::cout << "Device name " << dev.get_info<info::device::name>() << " "
              << "max_compute units"
              << " " << max_compute_units << ", Backend " << BE << "\n";

  void *hostp;
  posix_memalign(&hostp, 4096, transfer_upper_limit);
  memset(hostp, 1, transfer_upper_limit);

  if (prepare) {
    if (verbose)
      std::cout << "Doing L0 Import\n";
    sycl::ext::oneapi::experimental::prepare_for_device_copy(
        hostp, transfer_upper_limit, dq);
  }

  void *destp =
      malloc_device<char>(transfer_upper_limit, dq.get_device(), dq.get_context());
  dq.submit([&](handler &cgh) { cgh.memset(destp, 2, transfer_upper_limit); });
  dq.wait();

  if (run_host2dev) {
    if (!verbose)
      printf("SYCL USM API (%s)\n", BE);
    for (size_t s = transfer_lower_limit; s <= transfer_upper_limit; s <<= 1) {
      auto start_time = std::chrono::steady_clock::now();
      for (int i = 0; i < ntimes; ++i) {
        dq.submit([&](handler &cgh) { cgh.memcpy(destp, hostp, s); });
        dq.wait();
      }
      auto end_time = std::chrono::steady_clock::now();
      std::chrono::duration<double> seconds = end_time - start_time;

      if (verbose)
        printf("HosttoDevice: %8lu bytes, %7.3f ms, %8.3g GB/s\n", s,
               1000 * seconds.count() / ntimes,
               1e-9 * s / (seconds.count() / ntimes));
      else
        printf("%10.6f\n", 1e-9 * s / (seconds.count() / ntimes));
    }
  }

  if (run_dev2host) {
    if (!verbose)
      printf("SYCL USM API (%s)\n", BE);
    for (size_t s = transfer_lower_limit; s <= transfer_upper_limit; s <<= 1) {
      auto start_time = std::chrono::steady_clock::now();
      for (int i = 0; i < ntimes; ++i) {
        dq.submit([&](handler &cgh) { cgh.memcpy(hostp, destp, s); });
        dq.wait();
      }
      auto end_time = std::chrono::steady_clock::now();
      std::chrono::duration<double> seconds = end_time - start_time;

      if (verbose)
        printf("DeviceToHost: %8lu bytes, %7.3f ms, %8.3g GB/s\n", s,
               seconds.count(), 1e-9 * s / (seconds.count() / ntimes));
      else
        printf("%10.6f\n", 1e-9 * s / (seconds.count() / ntimes));
    }
  }

  if (prepare)
    sycl::ext::oneapi::experimental::release_from_device_copy(hostp, dq);

  free(hostp);
  free(destp, dq.get_context());
}

Compilation command:

icpx -fsycl sycl_prepare_bench.cpp

Example run command:

a.out -p -t h2d -s 256000000

The above run command specifies doing the prepare (-p), host-to-device (-t h2d), and transferring 256 million bytes (-s 256000000).

Date Transfer Rate Measurements

We use the program, sycl_prepare_bench.cpp, to measure the rate of data transfer between host and device (with and without prepare/release).

The transfer rate for a data size of 256 million bytes when running on the particular GPU used (1-stack only) was as follows.

Optimizing Data Transfers in OpenMP

In OpenMP, the import (prepare) and release are done using the register and unregister APIs provided as an Intel extension to OpenMP. They give the programmer explicit control over the address range and the duration of the import.

OpenMP Register and Unregister APIs

The interfaces for the OpenMP register and unregister APIs are as follows:

int ompx_target_register_host_pointer
    (void *HostPtr, size_t numBytes, int DeviceNum)

void ompx_target_unregister_host_pointer
    (void *HostPtr, int DeviceNum)

See Intel Compiler Extension Routines to OpenMP (C/C++) for a description of the APIs.

The OpenMP register and unregister APIs are similar to the SYCL prepare and release APIs. When using the APIs, the onus is on the user to ensure correctness and safety with respect to the lifetime ranges.

Notes:

• The register/unregister APIs can be called from Fortran as well as C/C++ code.

OpenMP Examples

We present below three OpenMP examples (in Fortran) to illustrate the effect of memory allocation on performance.

In the examples, the main computation is done in a loop with iter iterations, where iter is 2000.

A target data directive is used to map matrices a, b, and c to the device before the start of the loop, and copy matrix c from the device to the host at the end of the loop.

In each iteration of the loop, the elements of a and b are updated on the host and the new values are copied to the device using the target update directive. This is followed by a call to sgemm which is computed on the device. sgemm multiplies matrices a and b on the device and stores the result in matrix c on the device.

The main computation is shown in the following snippet of code.

        !$omp target data map(to: a, b) map(tofrom: c)

        do i = 1, iter
            ! Update arrays a and b on the host.
            a(:,:) = a(:,:) + 1
            b(:,:) = b(:,:) - 1

            ! Copy new values of a and b to the device.
            !$omp target update to (a, b)

            ! Compute sgemm on the device.
            !$omp dispatch
            call sgemm('n','n',m,n,k,alpha,a,m,b,k,beta,c,m)
        end do

        !$omp end target data

Memory allocation in each of the three OpenMP examples is described below.

Example 1: Allocate matrices in system memory

In the first OpenMP example, openmp_system_mem.f, the matrices a, b, and c are allocated in system memory using the Fortran allocate statement.

        allocate( a(1 : m, 1 : k) )
        allocate( b(1 : k, 1 : n) )
        allocate( c(1 : m, 1 : n) )

Example 2: Allocate matrices in host USM

In the second OpenMP example, openmp_host_usm.f, the matrices a, b, and c are allocated in host USM using the OpenMP allocators directive with the allocator omp_target_host_mem_alloc.

        !$omp allocators allocate(allocator(omp_target_host_mem_alloc): a)
        allocate( a(1 : m, 1 : k) )

        !$omp allocators allocate(allocator(omp_target_host_mem_alloc): b)
        allocate( b(1 : k, 1 : n) )

        !$omp allocators allocate(allocator(omp_target_host_mem_alloc): c)
        allocate( c(1 : m, 1 : n) )

Example 3: Allocate matrices in system memory and use register/unregister APIs

In the third OpenMP example, openmp_register_mem.f, the matrices a, b, and c are allocated in system memory using the Fortran allocate statement, just like in openmp_system_mem.f.

        allocate( a(1 : m, 1 : k) )
        allocate( b(1 : k, 1 : n) )
        allocate( c(1 : m, 1 : n) )

Right after the matrices are allocated, the memory for the matrices is registered (imported).

        stat = ompx_target_register_host_pointer(C_LOC(a),  &
               sizeof(a), device_num)
        stat = ompx_target_register_host_pointer(C_LOC(b),  &
               sizeof(b), device_num)
        stat = ompx_target_register_host_pointer(C_LOC(c),  &
               sizeof(c), device_num)

Before the matrices are deallocated, they are unregistered (released).

        call ompx_target_unregister_host_pointer(C_LOC(a), device_num)
        call ompx_target_unregister_host_pointer(C_LOC(b), device_num)
        call ompx_target_unregister_host_pointer(C_LOC(c), device_num)

Performance Comparison

We compare the performance of the three OpenMP examples openmp_sys_usm.f, openmp_host.f, and openmp_register_mem.f.

The compilation and run commands are as follows.

Compilation commands:

ifx -O3 -fiopenmp -fopenmp-targets=spir64 -qmkl -fpp -free openmp_system_mem.f -o openmp_system_mem.exe

ifx -O3 -fiopenmp -fopenmp-targets=spir64 -qmkl -fpp -free openmp_host_usm.f -o openmp_host_usm.e

ifx -O3 -fiopenmp -fopenmp-targets=spir64 -qmkl -fpp -free openmp_register_mem.f -o openmp_register_mem.exe

Example run commands:

OMP_TARGET_OFFLOAD=MANDATORY ZE_AFFINITY_MASK=0 ./openmp_system_mem.exe

OMP_TARGET_OFFLOAD=MANDATORY ZE_AFFINITY_MASK=0 ./openmp_host_usm.exe

OMP_TARGET_OFFLOAD=MANDATORY ZE_AFFINITY_MASK=0 ./openmp_register_mem.exe

The performance of the three versions when running on the particular GPU used (1-stack only) was as follows.

The above table shows that allocating the matrices in host USM (openmp_host_usm.f) performs better than allocating the matrices in system memory (openmp_system_mem.f).

The performance of the system memory version can be improved (openmp_register_mem.f) by calling the APIs, ompx_target_register_host_pointer() and ompx_target_unregister_host_pointer(), to register (import) the matrices before the computation in the loop and unregister (release) the matrices after the loop. As a result, the performance of openmp_register_mem.f matches that of openmp_host_usm.f.

Performance Recommendations

For repeated data transfers between host and device, we recommend the following approaches:

1. Allocate data that will be the source or destination of repeated data transfers between host and device in host Unified Shared Memory (USM), rather than in system memory. By allocating the data in host USM, the data transfer rate is optimal. To allocate data in host USM:

   • In SYCL, use the malloc_host API.

   • In OpenMP C/C++ and Fortran, use the omp_target_alloc_host API.

   • Alternatively, in OpenMP Fortran only, use the allocators directive with the allocator omp_target_host_mem_alloc.

2. If the above approach (1) cannot be applied, then import the system memory using the following APIs:

   • In SYCL, use the prepare_for_device_copy and release_from_device_copy APIs shown above.

   • In OpenMP (C/C++ and Fortran), use the ompx_target_register_host_pointer and ompx_target_unregister_host_pointer APIs shown above.

References

1. sycl_ext_oneapi_copy_optimize

2. Intel Compiler Extension Routines to OpenMP (C/C++)

3. Environment Variables — oneAPI DPC++ Compiler Documentation