ArrayFire Ruby Bindings
(Part VI : Device and Util)
22 August 2017 by
ArrayFire has Device and Util class that contains of methods which can be used to manage the CPU and GPU devices and various utility functions like printing and storing the arrays. This blog will explain my work regarding the bindings I have created and how to use them.
Device
Device class contains of singleton methods like info, device_gc, lock_device_ptr that can
be used to get info about the GPU devices used for calculation, explicitly call the garbage collector
and locking the pointers on GPU device.
The implementation is as follows:
void Init_arrayfire() {
ArrayFire = rb_define_module("ArrayFire");
Device = rb_define_class_under(ArrayFire, "Device", rb_cObject);
rb_define_singleton_method(Device, "info", (METHOD)arf_info, 0);
rb_define_singleton_method(Device, "init", (METHOD)arf_init2, 0);
rb_define_singleton_method(Device, "info_string", (METHOD)arf_info_string, 0);
rb_define_singleton_method(Device, "device_info", (METHOD)arf_device_info, 0);
rb_define_singleton_method(Device, "get_device_count", (METHOD)arf_get_device_count, 0);
rb_define_singleton_method(Device, "get_dbl_support", (METHOD)arf_get_dbl_support, 1);
rb_define_singleton_method(Device, "set_device", (METHOD)arf_set_device, 1);
rb_define_singleton_method(Device, "get_device", (METHOD)arf_get_device, 0);
rb_define_singleton_method(Device, "sync", (METHOD)arf_sync, 1);
rb_define_singleton_method(Device, "device_mem_info", (METHOD)arf_device_mem_info, 0);
rb_define_singleton_method(Device, "print_mem_info", (METHOD)arf_print_mem_info, 2);
rb_define_singleton_method(Device, "device_gc", (METHOD)arf_device_gc, 0);
rb_define_singleton_method(Device, "set_mem_step_size", (METHOD)arf_set_mem_step_size, 1);
rb_define_singleton_method(Device, "get_mem_step_size", (METHOD)arf_get_mem_step_size, 0);
rb_define_singleton_method(Device, "lock_device_ptr", (METHOD)arf_lock_device_ptr, 1);
rb_define_singleton_method(Device, "unlock_device_ptr", (METHOD)arf_unlock_device_ptr, 1);
rb_define_singleton_method(Device, "lock_array", (METHOD)arf_lock_array, 1);
rb_define_singleton_method(Device, "unlock_array", (METHOD)arf_unlock_array, 1);
rb_define_singleton_method(Device, "is_locked_array", (METHOD)arf_is_locked_array, 1);
rb_define_singleton_method(Device, "get_device_ptr", (METHOD)arf_get_device_ptr, 0);
}
The implementation of device_info is interesting as it has 4 return values in the form of strings.
ArrayFire::Device.device_info passes the variables to be returned to ArrayFire::Device.device_info_func
which modifies the contents of the variables passed.
module ArrayFire
class Device
def self.device_info
d_name = ""
d_platform = ""
d_toolkit = ""
d_compute = ""
ArrayFire::Device.device_info_func(d_name, d_platform, d_toolkit, d_compute);
return d_name, d_platform, d_toolkit, d_compute
end
end
end
The point to note here is that ArrayFire::Device.device_info uses rb_str_cat2() to concatenate the char*
to the VALUE containing empty string.
static VALUE arf_device_info(VALUE self, VALUE name_val, VALUE platform_val, VALUE toolkit_val, VALUE compute_val){
char* d_name = (char*)malloc(sizeof(char) * 64);
char* d_platform = (char*)malloc(sizeof(char) * 10);
char* d_toolkit = (char*)malloc(sizeof(char) * 64);
char* d_compute = (char*)malloc(sizeof(char) * 10);
af_device_info(d_name, d_platform, d_toolkit, d_compute);
rb_str_cat2(name_val, d_name);
rb_str_cat2(platform_val, d_platform);
rb_str_cat2(toolkit_val, d_toolkit);
rb_str_cat2(compute_val, d_compute);
return Qnil;
}
static VALUE arf_device_mem_info(VALUE self){
size_t alloc_bytes, alloc_buffers, lock_bytes, lock_buffers;
af_device_mem_info( &alloc_bytes, &alloc_buffers, &lock_bytes, &lock_buffers);
printf("Allocated Bytes: %d\nAllocated buffers: %d\nLock Bytes: %d\nLock Buffers: %d\n",
alloc_bytes, alloc_buffers, lock_bytes, lock_buffers);
return Qnil;
}
Running pry to check the bindings:
rake pry
pry -r './lib/arrayfire.rb'
[1] pry(main)> ArrayFire::Device.info
ArrayFire v3.4.0 (CUDA, 64-bit Linux, build 75cad40)
Platform: CUDA Toolkit 7.5, Driver: 375.66
[0] GeForce GTX 750 Ti, 4042 MB, CUDA Compute 5.0
=> nil
[2] pry(main)> ArrayFire::Device.device_info
=> ["GeForce_GTX_750_Ti", "CUDA", "v7.5", "5.0"]
[3] pry(main)> ArrayFire::Device.get_device_count
=> 1
[4] pry(main)> ArrayFire::Device.get_dbl_support(0)
=> true
[5] pry(main)> ArrayFire::Device.device_mem_info
Allocated Bytes: 0
Allocated buffers: 0
Lock Bytes: 0
Lock Buffers: 0
=> nil
[6] pry(main)> arr = ArrayFire::Af_Array.new 2, [4,4], [1, 2, 2, 0, -2, 2 , 1, 3, 1, 4, 3 , 1, 0, -3, 2, 9]
No Name Array
[4 4 1 1]
1.0000 -2.0000 1.0000 0.0000
2.0000 2.0000 4.0000 -3.0000
2.0000 1.0000 3.0000 2.0000
0.0000 3.0000 1.0000 9.0000
=> #<ArrayFire::Af_Array:0x000000023800c0>
[7] pry(main)> ArrayFire::Device.print_mem_info("mem info", 0)
mem info
---------------------------------------------------------
| POINTER | SIZE | AF LOCK | USER LOCK |
---------------------------------------------------------
| 0x702f80000 | 1 KB | Yes | No |
| 0x702f80400 | 1 KB | No | No |
---------------------------------------------------------
=> nil
[8] pry(main)> ArrayFire::Device.device_mem_info
Allocated Bytes: 2048
Allocated buffers: 2
Lock Bytes: 1024
Lock Buffers: 1
=> nil
[9] pry(main)> ArrayFire::Device.get_mem_step_size
=> 1024
[10] pry(main)> ArrayFire::Device.is_locked_array(arr)
=> false
[11] pry(main)> ArrayFire::Device.lock_array(arr)
=> true
[12] pry(main)> ArrayFire::Device.is_locked_array(arr)
=> true
Util
Util class contains of methods responsible for printing an Af_Array, saving it in a file or converting it to string and other utility methods.
The implementation is as follows:
void Init_arrayfire() {
ArrayFire = rb_define_module("ArrayFire");
Util = rb_define_class_under(ArrayFire, "Util", rb_cObject);
rb_define_singleton_method(Util, "print_array", (METHOD)arf_print_array, 1);
rb_define_singleton_method(Util, "print_array_gen", (METHOD)arf_print_array_gen, 0);
rb_define_singleton_method(Util, "save_array", (METHOD)arf_save_array, 4);
rb_define_singleton_method(Util, "read_array_index", (METHOD)arf_read_array_index, 0);
rb_define_singleton_method(Util, "read_array_key", (METHOD)arf_read_array_key, 0);
rb_define_singleton_method(Util, "read_array_key_check", (METHOD)arf_read_array_key_check, 0);
rb_define_singleton_method(Util, "array_to_string", (METHOD)arf_array_to_string, 4);
rb_define_singleton_method(Util, "get_version", (METHOD)arf_get_version, 0);
rb_define_singleton_method(Util, "get_revision", (METHOD)arf_get_revision, 0);
rb_define_singleton_method(Util, "get_size_of", (METHOD)arf_get_size_of, 1);
}
af_array_to_string API has also been used to implement ArrayFire::Af_Array#to_s.
The implementation of arf_get_version is interesting as it returns a hash value that represents
the version of ArrayFire C library installed using the keys as major, minor and patch.
rb_hash_new and rb_hash_aset has been used to create a hash.
static VALUE arf_print_array(VALUE self, VALUE input_val){
afstruct* input;
Data_Get_Struct(input_val, afstruct, input);
af_print_array(input->carray);
return Qtrue;
}
static VALUE arf_save_array(VALUE self, VALUE key_val, VALUE array_val, VALUE fn_val, VALUE append){
afstruct* input;
Data_Get_Struct(array_val, afstruct, input);
const char* key = StringValueCStr(key_val);
const char* filename = StringValueCStr(fn_val);
int index;
af_save_array (&index, key, input->carray, filename, RTEST(append));
return INT2NUM(index);
}
static VALUE arf_array_to_string(VALUE self, VALUE exp_val, VALUE array_val, VALUE precision, VALUE transpose){
char* output;
afstruct* input;
Data_Get_Struct(array_val, afstruct, input);
const char* exp = StringValueCStr(exp_val);
af_array_to_string(&output, exp, input->carray, NUM2INT(precision), RTEST(transpose));
return rb_str_new_cstr(output);
}
static VALUE arf_get_version(VALUE self){
int major, minor, patch;
af_get_version(&major, &minor, &patch);
VALUE hash = rb_hash_new();
rb_hash_aset(hash, rb_str_new_cstr("major"), INT2NUM(major));
rb_hash_aset(hash, rb_str_new_cstr("minor"), INT2NUM(minor));
rb_hash_aset(hash, rb_str_new_cstr("patch"), INT2NUM(patch));
return hash;
}
Lets use pry to check the bindings:
$ rake pry
pry -r './lib/arrayfire.rb'
[1] pry(main)> arr = ArrayFire::Af_Array.new 2, [4,4], [1, 2, 2, 0, -2, 2 , 1, 3, 1, 4, 3 , 1, 0, -3, 2, 9]
No Name Array
[4 4 1 1]
1.0000 -2.0000 1.0000 0.0000
2.0000 2.0000 4.0000 -3.0000
2.0000 1.0000 3.0000 2.0000
0.0000 3.0000 1.0000 9.0000
=> #<ArrayFire::Af_Array:0x000000026bde18>
[2] pry(main)> ArrayFire::Util.print_array(arr)
No Name Array
[4 4 1 1]
1.0000 -2.0000 1.0000 0.0000
2.0000 2.0000 4.0000 -3.0000
2.0000 1.0000 3.0000 2.0000
0.0000 3.0000 1.0000 9.0000
=> true
[3] pry(main)> x = ArrayFire::Util.array_to_string("GPU Array", arr, 5, false)
=> "GPU Array\n[4 4 1 1]\n 1.00000 2.00000 2.00000 0.00000 \n -2.00000 2.00000 1.00000 3.00000 \n 1.00000 4.00000 3.00000 1.00000 \n 0.00000 -3.00000 2.00000 9.00000 \n\n"
[4] pry(main)> puts x
GPU Array
[4 4 1 1]
1.00000 2.00000 2.00000 0.00000
-2.00000 2.00000 1.00000 3.00000
1.00000 4.00000 3.00000 1.00000
0.00000 -3.00000 2.00000 9.00000
=> nil
[5] pry(main)> ArrayFire::Util.get_version
=> {"major"=>3, "minor"=>4, "patch"=>0}
[6] pry(main)> ArrayFire::Util.get_revision
=> "75cad40"
[7] pry(main)> ArrayFire::Util.get_size_of(:f64)
=> 8
The bindings work!.
Conclusion
We can easily manage the available GPU devices and manage the memory. Also, we can save the Af_Array
output to a file among other utilities.
In the next blog post, I will explain about using multiple backends using ArrayFire , i.e. OpenCL, CUDA
and even use CPUs.
