2. Basic Usage¶
Futhark contains several code generation backends. Each is provided
as subcommand of the
futhark binary. For example,
compiles a Futhark program by translating it to sequential C code,
futhark pyopencl generates Python code with calls to the
PyOpenCL library. The different compilers all contain the same
frontend and optimisation pipeline - only the code generator is
different. They all provide roughly the same command line interface,
but there may be minor differences and quirks due to characteristics
of the specific backends.
There are two main ways of compiling a Futhark program: to an
executable (by using
--executable, which is the default), and to a
--library). Executables can be run immediately, but are
useful mostly for testing and benchmarking. Libraries can be called
from non-Futhark code.
2.1. Compiling to Executable¶
A Futhark program is stored in a file with the extension
can be compiled to an executable program as follows:
$ futhark c prog.fut
This makes use of the
futhark c compiler, but any other will work
as well. The compiler will automatically invoke
gcc to produce an
executable binary called
prog. If we had used
futhark c, the
prog file would instead have
contained Python code, along with a shebang for easy execution. In
general, when compiling file
foo.fut, the result will be written
to a file
foo (i.e. the extension will be stripped off). This can
be overridden using the
-o option. For more details on specific
compilers, see their individual manual pages.
Executables generated by the various Futhark compilers share a common
command-line interface, but may also individually support more
options. When a Futhark program is run, execution starts at one of
its entry points. By default, the entry point named
run. An alternative entry point can be indicated by using the
option. All entry point functions must be declared appropriately in
the program (see Entry Points). If the entry point takes any
parameters, these will be read from standard input in a subset of the
Futhark syntax. A binary input format is also supported; see
Binary Data Format. The result of the entry point is printed
to standard output.
Only a subset of all Futhark values can be passed to an executable. Specifically, only primitives and arrays of primitive types are supported. In particular, nested tuples and arrays of tuples are not permitted. Non-nested tuples are supported are supported as simply flat values. This restriction is not present for Futhark programs compiled to libraries. If an entry point returns any such value, its printed representation is unspecified. As a special case, an entry point is allowed to return a flat tuple.
Instead of compiling, there is also an interpreter, accessible as
futhark run and
futhark repl. The latter is an interactive
prompt, useful for experimenting with Futhark expressions. Be aware
that the interpreter runs code very slowly.
2.1.1. Executable Options¶
All generated executables support the following options.
-t FILEPrint the time taken to execute the program to the indicated file, an integral number of microseconds. The time taken to perform setup or teardown, including reading the input or writing the result, is not included in the measurement. See the documentation for specific compilers to see exactly what is measured.
-r RUNSRun the specified entry point the given number of times (plus a warmup run). The program result is only printed once, after the last run. If combined with
-t, one measurement is printed per run. This is a good way to perform benchmarking.
-DPrint debugging information on standard error. Exactly what is printed, and how it looks, depends on which Futhark compiler is used. This option may also enable more conservative (and slower) execution, such as frequently synchronising to check for errors.
-bPrint the result using the binary data format (Binary Data Format). For large outputs, this is significantly faster and takes up less space.
22.214.171.124. Parallel Options¶
The following options are supported by executables generated with the
parallel backends (
--tuning=FILELoad tuning options from the indicated tuning file. The file must contain lines of the form
SIZE=VALUE, where each SIZE must be one of the sizes listed by the
--print-sizesoption (without size class), and the VALUE must be a non-negative integer. Extraneous spaces or blank lines are not allowed. A zero means to use the default size, whatever it may be. In case of duplicate assignments to the same size, the last one takes predecence. This is equivalent to passing each size setting on the command like using the
--sizeoption, but more convenient.
--print-sizesPrint a list of tunable sizes followed by their size class in parentheses, which indicates what they are used for.
--size=SIZE=VALUESet one of the tunable sizes to the given value. Using the
--tuningoption is more convenient.
126.96.36.199. OpenCL-specific Options¶
The following options are supported by executables generated with the
OpenCL backends (
-p PLATFORMPick the first OpenCL platform whose name contains the given string. The special string
kis an integer, can be used to pick the k-th platform, numbered from zero.
-d DEVICEPick the first OpenCL device whose name contains the given string. The special string
kis an integer, can be used to pick the k-th device, numbered from zero. If used in conjunction with
-p, only the devices from matching platforms are considered.
--dump-opencl FILEDon’t run the program, but instead dump the embedded OpenCL program to the indicated file. Useful if you want to see what is actually being executed.
--load-opencl FILEInstead of using the embedded OpenCL program, load it from the indicated file. This is extremely unlikely to result in succesful execution unless this file is the result of a previous call to
--dump-opencl(perhaps lightly modified).
--dump-opencl-binary FILEDon’t run the program, but instead dump the compiled version of the embedded OpenCL program to the indicated file. On NVIDIA platforms, this will be PTX code. If this option is set, no entry point will be run.
--load-opencl-binary FILELoad an OpenCL binary from the indicated file.
--build-option OPTAdd an additional build option to the string passed to
clBuildProgram(). Refer to the OpenCL documentation for which options are supported. Be careful - some options can easily result in invalid results.
There is rarely a need to use both
-d. For example, to
run on the first available NVIDIA GPU,
-p NVIDIA is sufficient, as
there is likely only a single device associated with this platform.
On *nix (including macOS), the clinfo tool (available in many package
managers) can be used to determine which OpenCL platforms and devices
are available on a given system. On Windows, CPU-z can be used.
188.8.131.52. CUDA-specific Options¶
The following options are supported by executables generated by the
--dump-cuda FILEDon’t run the program, but instead dump the embedded CUDA program to the indicated file. Useful if you want to see what is actually being executed.
--load-cuda FILEInstead of using the embedded CUDA program, load it from the indicated file. This is extremely unlikely to result in succesful execution unless this file is the result of a previous call to
--dump-cuda(perhaps lightly modified).
--dump-cuda, but dumps the compiled PTX code instead.
--load-ptx FILEInstead of using the embedded CUDA program, load compiled PTX code from the indicated file.
--nvrtc-option=OPTAdd the given option to the command line used to compile CUDA kernels with NVRTC. The list of supported options varies with the CUDA version but can be found in the NVRTC documentation.
2.2. Compiling to Library¶
While compiling a Futhark program to an executable is useful for
testing, it is not suitable for production use. Instead, a Futhark
program should be compiled into a reusable library in some target
language, enabling integration into a larger program. Five of the
Futhark compilers support this:
futhark py, and
2.2.1. General Concerns¶
Futhark entry points are mapped to some form of function or method in the target language. Generally, an entry point taking n parameters will result in a function taking n parameters. Extra parameters may be added to pass in context data, or out-parameters for writing the result, for target languages that do not support multiple return values from functions.
Not all Futhark types can be mapped cleanly to the target language. Arrays of tuples, for example, are a common issue. In such cases, opaque types are used in the generated code. Values of these types cannot be directly inspected, but can be passed back to Futhark entry points. In the general case, these types will be named with a random hash. However, if you insert an explicit type annotation (and the type name contains only characters valid for identifiers for the used backend), the indicated name will be used. Note that arrays contain brackets, which are usually not valid in identifiers. Defining a simple type alias is the best way around this.
2.2.2. Generating C¶
A Futhark program
futlib.fut can be compiled to reusable C code
$ futhark c --library futlib.fut
$ futhark opencl --library futlib.fut
This produces two files in the current directory:
futlib.h. If we wish (and are on a Unix system), we can then
futlib.c to a shared library like this:
$ gcc dotprod.c -o libdotprod.so -fPIC -shared
However, details of how to link the generated code with other C code is highly system-dependent, and outside the scope of this manual.
The generated header file (here,
futlib.h) specifies the API, and
is intended to be human-readable. The basic usage revolves around
creating a configuration object, which can then be used to obtain a
context object, which must be passed whenever entry points are
The configuration object is created using the following function:
struct futhark_context_config *futhark_context_config_new();
Depending on the backend, various functions are generated to modify the configuration. The following is always available:
void futhark_context_config_set_debugging(struct futhark_context_config *cfg, int flag);
A configuration object can be used to create a context with the following function:
struct futhark_context *futhark_context_new(struct futhark_context_config *cfg);
Memory management is entirely manual. Deallocation functions are provided for all types defined in the header file. Everything returned by an entry point must be manually deallocated.
Functions that can fail return an integer: 0 on success and a non-zero value on error. A human-readable string describing the error can be retrieved with the following function:
char *futhark_context_get_error(struct futhark_context *ctx);
It is the caller’s responsibility to
free() the returned string.
Any subsequent call to the function returns
NULL, until a new
For now, many internal errors, such as failure to allocate memory,
will cause the function to
abort() rather than return an error
code. However, all application errors (such as bounds and array size
checks) will produce an error code.
The API functions are thread safe.
184.108.40.206. C with OpenCL¶
When generating C code with
futhark opencl (which is likely the
common case), extra API functions are provided for directly accessing
or providing the OpenCL objects used by Futhark. Take care when using
these functions. In particular, a Futhark context can now be provided
with the command queue to use:
struct futhark_context *futhark_context_new_with_command_queue(struct futhark_context_config *cfg, cl_command_queue queue);
cl_command_queue specifies an OpenCL device, this is also how
manual platform and device selection is possible. A function is also
provided for retrieving the command queue used by some Futhark
cl_command_queue futhark_context_get_command_queue(struct futhark_context *ctx);
This can be used to connect two separate Futhark contexts that have been loaded dynamically.
cl_mem object underlying a Futhark array can be accessed
with the function named
depends on the array in question. For example:
cl_mem futhark_values_raw_i32_1d(struct futhark_context *ctx, struct futhark_i32_1d *arr);
The array will be stored in row-major form in the returned memory
object. The function performs no copying, so the
belongs to Futhark, and may be reused for other purposes when the
corresponding array is freed. A dual function can be used to
construct a Futhark array from a
struct futhark_i32_1d *futhark_new_raw_i32_1d(struct futhark_context *ctx, cl_mem data, int offset, int dim0);
This function does copy the provided memory into fresh internally
allocated memory. The array is assumed to be stored in row-major form
offset bytes into the memory region.
2.2.3. Generating Python¶
futhark py and
futhark pyopencl compilers both support
generating reusable Python code, although the latter of these
generates code of sufficient performance to be worthwhile. The
following mentions options and parameters only available for
futhark pyopencl. You will need at least PyOpenCL version 2015.2.
We can use
futhark pyopencl to translate the program
futlib.fut into a Python module
futlib.py with the following
$ futhark pyopencl --library futlib.fut
This will create a file
futlib.py, which contains Python code that
defines a class named
futlib. This class defines one method for
each entry point function (see Entry Points) in the Futhark
program. The methods take one parameter for each parameter in the
corresponding entry point, and return a tuple containing a value for
every value returned by the entry point. For entry points returning a
single (non-tuple) value, just that value is returned (that is,
single-element tuples are not returned).
After the class has been instantiated, these methods can be invoked to run the corresponding Futhark function. The constructor for the class takes various keyword parameters:
True(the default is
False), show a menu of available OpenCL platforms and devices, and use the one chosen by the user.
platform_pref=STRUse the first platform that contains the given string. Similar to the
-poption for executables.
device_pref=STRUse the first device that contains the given string. Similar to the
-doption for executables.
Futhark arrays are mapped to either the Numpy
ndarray type or the
type. Scalars are mapped to Numpy scalar types.