24 bit integers - poor performance / high cpu use

Hdf-forum archives
1

Gday,

I'm using 24 bit integers with HDF5 but finding the performance very poor.

I'm new to HDF5. I'm evaluating the format for use with a radio telescope.
The telescope will produce about 7TB per 12 hours of raw data, so space and
write efficiency are important.

The telescope system produces 24 bit signed integers. If we convert to 32
bits our files will grow by 33%, ie over 9.5TB instead of 7TB.

I successfully wrote 24 bit integers with HDF5. Unfortunately the writing is
very inefficient: the CPU sits at 100% and the write rate (in integers per
second) is about five times slower than with 32 bit ints, even though the
file is smaller. The file writing is CPU-bound: the disk is hardly working
at all, unlike with 32 bits where it's disk-bound.

It appears that the conversion from 32 bits in memory to 24 bits by the
library is very inefficient. I've done this with my own code and it's
possible to do very quickly so the writing is still disk-bound. In all cases
I'm using little-endian as my platform is Intel.

Is it possible to tune HDF5 to write 24 bit integers more efficiently? I've
included code snippets below.

Cheers,
Jay.

void write_integration_hdf5(struct cmac_cells* cmac, struct
corr_packet_header* header, hid_t f) {
static hid_t datatype = -1;
static hid_t dataspace = -1;

// We use either 32 or 24 bit types for values, according to args. 24 bit is
custom made.
if (datatype < 0) {
if (arg_24bits) {
// Define an HDF5 custom type for 24 bit int, little-endian (actually,
native)
datatype = H5Tcopy(H5T_NATIVE_INT32);
H5Tset_size(datatype, 3); //3 bytes
if (datatype < 0) {
fprintf(stderr, "Error creating HDF5 24 bit int type\n");
exit(-1);
}
} else {
datatype = H5T_NATIVE_INT32;
}
}

// Define the HDF5 dataspace, ie the rank and size of the dataset array
if (dataspace < 0) {
int rank = 2; //baseline x re/im
hsize_t dims[] = {NUM_CMAC_CELLS*NUM_VIS_PER_CELL, 2};
dataspace = H5Screate_simple(rank, dims, dims);
if (dataspace < 0) {
fprintf(stderr, "Error creating HDF5 dataspace\n");
exit(-1);
}
}

// Add a dataset
char name[50];
sprintf(name, "INT%d_FREQ%d", header->integration_num, header->frequency);
hid_t dataset = H5Dcreate(f, name, datatype, dataspace, H5P_DEFAULT);
if (dataset < 0) {
fprintf(stderr, "Error creating dataset %s\n", name);
exit(-1);
}

// Write the vis data to the new dataset
const char* buffer = (const char*)cmac->cells;
if (H5Dwrite(dataset, H5T_NATIVE_INT32, H5S_ALL, H5S_ALL, H5P_DEFAULT,
buffer) < 0) {
fprintf(stderr, "Error writing to dataset %s\n", name);
exit(-1);
}

// Close the dataset
H5Dclose(dataset);

2

Greetings Jay,

Jay Banyer wrote:

Gday,

I’m using 24 bit integers with HDF5 but finding the performance
very poor.

I’m new to HDF5. I’m evaluating the format for use with a radio
telescope. The telescope will produce about 7TB per 12 hours of raw
data, so space and write efficiency are important.

The telescope system produces 24 bit signed integers. If we
convert to 32 bits our files will grow by 33%, ie over 9.5TB instead of
7TB.

I
presume you have no requirement to use 24 bit integers other than to
save space and time, i.e. no odd ball processor that use 24 bits for
arithmetic, etc. Here are some suggestions:

Are you using the internal HDF5 compression? If not, I suggest
compressing your 9.5TB 32 bit integer files to see how much space you
save. Using internal compression will ultimately save you time as well
as it reduces the amount of data being pushed across the slow disk
channel. You can test this very easily using the h5repack
utility which reduces your programming effort to selecting command line
options. You will likely need to play with chunking parameters. Read
the documentation on chunking, ask on the forum if you are still
confused. If you can find a satisfactory set of settings you’ll need
to modify your (presumably) C code to turn on the compression filter
prior to the disk writes. You might also find adding the shuffle
filter helps since the upper byte of every 32 bit word will have one of
two values.

HDF5 has a scale and offset filter. I personally dislike this approach
for floats because it is lossy, but since you have integer data it
might be right in this situation. h5repack can, apparently,
let you apply this filter as well.

In both cases the end user of the data file will not need to know which
filters were used. The HDF5 library will automatically apply the
correct reverse filter when the data are read back in.

More generally, a hint for evaluating HDF5 is to start by using a high
level language interface. Python has an excellent open source
interface, h5py; and the commercial packages Matlab and IDL include an
interface as well. These interfaces deal with a lot of the bookkeeping
for you so that you can concentrate on evaluating your data format
without getting bogged down in the details of the C API.

Cheers,

–dan

··· 
-- Daniel Kahn
Science Systems and Applications Inc.
301-867-2162
3

Hi Jay,

I am saving and loading floats converting them to 16-bit half floats in HDF5
quite efficiently, therefore I am pretty sure you can do it with your data.
I may be blind but I do not see where you register your conversion
functions, or is it that you expect HDF5 to convert implicitly by
truncating? Maybe this is where your code is not efficient?

HTH

Dimitris Servis

P.S. I have found that for large datasets (like yours) of reduced precision
numbers that you need to store for later post processing and don't need to
keep in memory it is more efficient to make in-place conversion and then
write to HDF5 using the reduced datatype.

···

2011/3/18 Jay Banyer <jay@physics.usyd.edu.au>

Gday,

I'm using 24 bit integers with HDF5 but finding the performance very poor.

I'm new to HDF5. I'm evaluating the format for use with a radio telescope.
The telescope will produce about 7TB per 12 hours of raw data, so space and
write efficiency are important.

The telescope system produces 24 bit signed integers. If we convert to 32
bits our files will grow by 33%, ie over 9.5TB instead of 7TB.

I successfully wrote 24 bit integers with HDF5. Unfortunately the writing
is very inefficient: the CPU sits at 100% and the write rate (in integers
per second) is about five times slower than with 32 bit ints, even though
the file is smaller. The file writing is CPU-bound: the disk is hardly
working at all, unlike with 32 bits where it's disk-bound.

It appears that the conversion from 32 bits in memory to 24 bits by the
library is very inefficient. I've done this with my own code and it's
possible to do very quickly so the writing is still disk-bound. In all cases
I'm using little-endian as my platform is Intel.

Is it possible to tune HDF5 to write 24 bit integers more efficiently? I've
included code snippets below.

Cheers,
Jay.

void write_integration_hdf5(struct cmac_cells* cmac, struct
corr_packet_header* header, hid_t f) {
static hid_t datatype = -1;
static hid_t dataspace = -1;

// We use either 32 or 24 bit types for values, according to args. 24 bit
is custom made.
if (datatype < 0) {
if (arg_24bits) {
// Define an HDF5 custom type for 24 bit int, little-endian (actually,
native)
datatype = H5Tcopy(H5T_NATIVE_INT32);
H5Tset_size(datatype, 3); //3 bytes
if (datatype < 0) {
fprintf(stderr, "Error creating HDF5 24 bit int type\n");
exit(-1);
}
} else {
datatype = H5T_NATIVE_INT32;
}
}

// Define the HDF5 dataspace, ie the rank and size of the dataset array
if (dataspace < 0) {
int rank = 2; //baseline x re/im
hsize_t dims[] = {NUM_CMAC_CELLS*NUM_VIS_PER_CELL, 2};
dataspace = H5Screate_simple(rank, dims, dims);
if (dataspace < 0) {
fprintf(stderr, "Error creating HDF5 dataspace\n");
exit(-1);
}
}

// Add a dataset
char name[50];
sprintf(name, "INT%d_FREQ%d", header->integration_num,
header->frequency);
hid_t dataset = H5Dcreate(f, name, datatype, dataspace, H5P_DEFAULT);
if (dataset < 0) {
fprintf(stderr, "Error creating dataset %s\n", name);
exit(-1);
}

// Write the vis data to the new dataset
const char* buffer = (const char*)cmac->cells;
if (H5Dwrite(dataset, H5T_NATIVE_INT32, H5S_ALL, H5S_ALL, H5P_DEFAULT,
buffer) < 0) {
fprintf(stderr, "Error writing to dataset %s\n", name);
exit(-1);
}

// Close the dataset
H5Dclose(dataset);

_______________________________________________
Hdf-forum is for HDF software users discussion.
Hdf-forum@hdfgroup.org
http://mail.hdfgroup.org/mailman/listinfo/hdf-forum_hdfgroup.org

4

Hi Jay,

Gday,

I'm using 24 bit integers with HDF5 but finding the performance very poor.

I'm new to HDF5. I'm evaluating the format for use with a radio telescope. The telescope will produce about 7TB per 12 hours of raw data, so space and write efficiency are important.

The telescope system produces 24 bit signed integers. If we convert to 32 bits our files will grow by 33%, ie over 9.5TB instead of 7TB.

I successfully wrote 24 bit integers with HDF5. Unfortunately the writing is very inefficient: the CPU sits at 100% and the write rate (in integers per second) is about five times slower than with 32 bit ints, even though the file is smaller. The file writing is CPU-bound: the disk is hardly working at all, unlike with 32 bits where it's disk-bound.

It appears that the conversion from 32 bits in memory to 24 bits by the library is very inefficient. I've done this with my own code and it's possible to do very quickly so the writing is still disk-bound. In all cases I'm using little-endian as my platform is Intel.

Is it possible to tune HDF5 to write 24 bit integers more efficiently? I've included code snippets below.

  You are falling into the "generic" integer <-> integer conversion code (used for unusual conversions), which has never been systematically optimized. If you have time to investigate the HDF5 library's code, I can point you toward the section of the library that does this. You might want to define your own datatype conversion routine that is specific for this particular type conversion. You would use H5Tregister (http://www.hdfgroup.org/HDF5/doc/RM/RM_H5T.html#Datatype-Register) for this.

  Quincey

···

On Mar 17, 2011, at 11:48 PM, Jay Banyer wrote:

Cheers,
Jay.

void write_integration_hdf5(struct cmac_cells* cmac, struct corr_packet_header* header, hid_t f) {
  static hid_t datatype = -1;
  static hid_t dataspace = -1;

  // We use either 32 or 24 bit types for values, according to args. 24 bit is custom made.
  if (datatype < 0) {
    if (arg_24bits) {
      // Define an HDF5 custom type for 24 bit int, little-endian (actually, native)
      datatype = H5Tcopy(H5T_NATIVE_INT32);
      H5Tset_size(datatype, 3); //3 bytes
      if (datatype < 0) {
        fprintf(stderr, "Error creating HDF5 24 bit int type\n");
        exit(-1);
      }
    } else {
      datatype = H5T_NATIVE_INT32;
    }
  }

  // Define the HDF5 dataspace, ie the rank and size of the dataset array
  if (dataspace < 0) {
    int rank = 2; //baseline x re/im
    hsize_t dims[] = {NUM_CMAC_CELLS*NUM_VIS_PER_CELL, 2};
    dataspace = H5Screate_simple(rank, dims, dims);
    if (dataspace < 0) {
      fprintf(stderr, "Error creating HDF5 dataspace\n");
      exit(-1);
    }
  }

  // Add a dataset
  char name[50];
  sprintf(name, "INT%d_FREQ%d", header->integration_num, header->frequency);
  hid_t dataset = H5Dcreate(f, name, datatype, dataspace, H5P_DEFAULT);
  if (dataset < 0) {
    fprintf(stderr, "Error creating dataset %s\n", name);
    exit(-1);
  }

  // Write the vis data to the new dataset
  const char* buffer = (const char*)cmac->cells;
  if (H5Dwrite(dataset, H5T_NATIVE_INT32, H5S_ALL, H5S_ALL, H5P_DEFAULT, buffer) < 0) {
    fprintf(stderr, "Error writing to dataset %s\n", name);
    exit(-1);
  }

  // Close the dataset
  H5Dclose(dataset);

_______________________________________________
Hdf-forum is for HDF software users discussion.
Hdf-forum@hdfgroup.org
http://mail.hdfgroup.org/mailman/listinfo/hdf-forum_hdfgroup.org