Project

BOAST

0.01
No release in over 3 years
Low commit activity in last 3 years
BOAST aims at providing a framework to metaprogram, benchmark and validate computing kernels
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
 Dependencies

Runtime

>= 1.9.3, ~> 1.9
>= 0.3.0, ~> 0.3
>= 0.6.0.8, ~> 0.6.0
>= 1.2.0, ~> 1.2
>= 1.3.2, ~> 1.3
>= 0.9.6, ~> 0.9
>= 1.0.0, ~> 1.0
>= 0.9
>= 0.5.1, ~> 0.5
>= 2.2.0, ~> 2
 Project Readme

BOAST

This section will present some simple examples to familiarize the user with BOAST. More samples can be found in the git repository.

Documentation can be found here: http://www.rubydoc.info/github/Nanosim-LIG/boast/master .

Testing

Test BOAST right away by looking at the interactive tutorials:

Simple Tutorial

Advanced Tutorial

Installation

BOAST is ruby based, so ruby needs to be installed on the machine. Installation of boast can be done using the ruby built-in package manager: gem. See following Listing for reference.

sudo apt-get install ruby ruby-dev
gem install --user-install BOAST

Variable and Procedure Declaration

The following samples are presented using irb ruby interactive interpreter. It can be launched using the irb command in a terminal. Following Listing shows the declaration of two variables of different kind.

irb(main):001:0> require 'BOAST'
=> true
irb(main):002:0> a = BOAST::Int "a"
=> a
irb(main):003:0> b = BOAST::Real "b"
=> b
irb(main):004:0> BOAST::decl a, b
integer(kind=4) :: a
real(kind=8) :: b
=> [a, b]

Following Listing shows the declaration of a procedure using the two previous variables as parameters. For clarity irb echoes have been suppressed.

005:0> p = BOAST::Procedure( "test_proc", [a,b] )
006:0> BOAST::opn p
SUBROUTINE test_proc(a, b)
  integer, parameter :: wp=kind(1.0d0)
  integer(kind=4) :: a
  real(kind=8) :: b
007:0> BOAST::close p
END SUBROUTINE test_proc

Switching Language

Following Listing shows how to switch BOAST to C. Available languages are FORTRAN, C, CUDA and CL.

008:0> BOAST::lang = BOAST::C
009:0> BOAST::opn p
void test_proc(int32_t a, double b){
010:0> BOAST::close p
}

Defining a Complete Procedure

Following Listing shows how to define a procedure and the associated code. Note that here the parameters of the procedure have been associated a direction: one, a, is an input parameter while the other, b, is an output parameter.

011:0> BOAST::lang = BOAST::FORTRAN
012:0> a = BOAST::Real( "a", :dir => :in)
013:0> b = BOAST::Real( "b", :dir => :out)
014:0> p = BOAST::Procedure( "plus_two", [a,b] ) {
015:1*   BOAST::pr b === a + 2
016:1> }
017:0> BOAST::pr p
SUBROUTINE plus_two(a, b)
  integer, parameter :: wp=kind(1.0d0)
  real(kind=8), intent(in) :: a
  real(kind=8), intent(out) :: b
  b = a + 2
END SUBROUTINE plus_two
018:0> BOAST::lang = BOAST::C
019:0> BOAST::pr p
void plus_two(const double a, double * b){
  (*b) = a + 2;
}

Creating, Building and Running a Computing Kernel

Following Listing shows how to create a Computing kernel (CKernel) and build it. Once a computing kernel is instantiated the output of BOAST will be redirected to the computing kernel source code. Line 4 sets the entry point of the computing kernel to the procedure we just defined. By default compilation commands are not shown unless an error occurs. This behavior can be changed by switching to verbose mode.

When running the kernel all the arguments have to be specified. Running a kernel returns a hash table containing information about the procedure execution. In this simple case two informations are returned, first the value of the output parameter b and second the time the kernel execution took.

020:0> BOAST::lang = BOAST::FORTRAN
021:0> k = BOAST::CKernel::new
022:0> BOAST::pr p
023:0> k.procedure = p
024:0> puts k
SUBROUTINE plus_two(a, b)
  integer, parameter :: wp=kind(1.0d0)
  real(kind=8), intent(in) :: a
  real(kind=8), intent(out) :: b
  b = a + 2
END SUBROUTINE plus_two
025:0> k.build
026:0> BOAST::verbose = true
027:0> k.build
gcc -O2 -Wall -fPIC -I/usr/lib/x86_64-linux-gnu/ruby/2.1.0 -I/usr/include/ruby-2.1.0 -I/usr/include/ruby-2.1.0/x86_64-linux-gnu -I/usr/include/x86_64-linux-gnu/ruby-2.1.0 -I/var/lib/gems/2.1.0/gems/narray-0.6.1.1 -DHAVE_NARRAY_H -c -o /tmp/Mod_plus_two20150309_4611_5a129k.o /tmp/Mod_plus_two20150309_4611_5a129k.c
gfortran -O2 -Wall -fPIC -c -o /tmp/plus_two20150309-4611-5a129k.o /tmp/plus_two20150309-4611-5a129k.f90
gcc -shared -o /tmp/Mod_plus_two20150309_4611_5a129k.so /tmp/Mod_plus_two20150309_4611_5a129k.o /tmp/plus_two20150309-4611-5a129k.o -Wl,-Bsymbolic-functions -Wl,-z,relro -rdynamic -Wl,-export-dynamic -L/usr/lib -lruby-2.1 -lrt
028:0> r = k.run(5,0)
029:0> puts r
{:reference_return=>{:b=>7.0}, :duration=>5.84e-07}

Using Arrays in Procedures

Most computing kernels don't work on scalar values but rather on arrays of data. Following Listing shows how to use arrays in computing kernels. In this case we place ourselves in BOAST namespace to reduce the syntax overhead. Variables a and b are one-dimensional arrays of size n. Arrays in BOAST start at index 1 unless specified otherwise. For instance Dim(0,n-1) would have created a dimension starting at 0. Array bounds can also be negative and several dimensions can be specified to obtain muti-dimensional arrays. For self contained procedures/kernels one can use the shortcut written on line 13 to create a CKernel object. As we are not specifying build options the build command can also be omitted and will be automatically called when running the kernel the first time. Lines 17 to 19 are used to check the result of the kernel.

001:0> require 'BOAST'
002:0> require 'narray'
003:0> include BOAST
004:0> n = Int(  "n", :dir => :in )
005:0> a = Real( "a", :dir => :in,  :dim => [Dim(n)] )
006:0> b = Real( "b", :dir => :out, :dim => [Dim(n)] )
007:0> p = Procedure( "plus_two", [n, a, b] ) {
008:1*   decl i = Int( "i" )
009:1>   pr For( i, 1, n ) {
010:2*     pr b[i] === a[i] + 2.0
011:2>   }
012:1> }
013:0> k = p.ckernel
014:0> input  = NArray.float(1024).random
015:0> output = NArray.float(1024)
016:0> k.run(input.length, input, output)
017:0> (output - input).each { |val|
018:1*   raise "Error!" if (val-2).abs > 1e-15
019:1> }
020:0> stats = k.run(input.length, input, output)
021:0> puts "Success, duration: #{stats[:duration]} s"
Success, duration: 3.79e-06 s

The Canonical Case: Vector Addition

Following Listing shows the addition of two vectors in a third one. Here BOAST is configured to have arrays starting at 0 and to use single precision reals by default (Lines 5 and 6). The kernel declaration is encapsulated inside a method to avoid cluttering the global namespace. Line 15 the expression c[i] === a[i]+ b[i] is stored inside a variable expr for later use. Lines 16 to 23 show that the kernel differs depending on the target language, in CUDA and OpenCL each thread will process one element.

require 'narray'
require 'BOAST'
include BOAST

set_array_start(0)
set_default_real_size(4)

def vector_add
  n = Int("n",:dir => :in)
  a = Real("a",:dir => :in, :dim => [ Dim(n)] )
  b = Real("b",:dir => :in, :dim => [ Dim(n)] )
  c = Real("c",:dir => :out, :dim => [ Dim(n)] )
  p = Procedure("vector_add", [n,a,b,c]) {
    decl i = Int("i")
    expr = c[i] === a[i] + b[i]
    if (get_lang == CL or get_lang == CUDA) then
      pr i === get_global_id(0)
      pr expr
    else
      pr For(i,0,n-1) {
        pr expr
      }
    end
  }
  return p.ckernel
end

Following Listing shows the a way to check the validity of the previous kernel over the available range of languages. The options that are passed to run are only relevant for GPU languages and are thus ignored in FORTRAN and C (Line 16). Success is only printed if results are validated, else an exception is raised (Lines 17 to 20).

n = 1024*1024
a = NArray.sfloat(n).random
b = NArray.sfloat(n).random
c = NArray.sfloat(n)

epsilon = 10e-15

c_ref = a + b

[:FORTRAN, :C, :CL, :CUDA].each { |l|
  set_lang( BOAST.const_get(l)  )
  puts "#{l}:"
  k = vector_add
  puts k.print
  c.random!
  k.run(n, a, b, c, :global_work_size => [n,1,1], :local_work_size => [32,1,1])
  diff = (c_ref - c).abs
  diff.each { |elem|
    raise "Warning: residue too big: #{elem}" if elem > epsilon
  }
}
puts "Success!"

Options

Options can be passed through environment variables. Most BOAST states can be set this way. Nonetheless here is a list of the most used ones, their possible values:

  • BOAST_LANG: can be C, FORTRAN, OpenCL or CUDA

Compiler related:

  • CC: c compiler
  • CFLAGS: c compiler flags
  • FC: fortran compiler
  • FCFLAGS: fortran compiler flags
  • CXX: c++ compiler
  • CXXFLAGS: c++ compiler flags
  • LD: linker (default CC)
  • LDFLAGS: linker flags
  • NVCC: cuda compiler
  • NVCCFLAGS: cuda compiler flags

OpenCL related:

  • CLFLAGS: OpenCL compilation flags
  • CLPLATFORM: restricts OpenCL platforms to those that with matching CL_PLATFORM_NAME property
  • CLVENDOR: restricts OpenCL platforms to those that with matching CL_PLATFORM_VENDOR property
  • CLDEVICE: restricts OpenCL devices to those that with matching CL_DEVICE__NAME property
  • CLDEVICETYPE: can be CPU, GPU, ACCELERATOR, CUSTOM, DEFAULT or ALL

Debug Related:

  • VERBOSE: anything else than false or nil should enable, print compilation lines
  • DEBUG_SOURCE: print source files before compiling them
  • KEEP_TEMP: keep temporary files
  • INSPECT: allow boast reflexive inspect
  • DISABLE_OPENMP: forcibly disable OpenMP

Architecture related:

  • MODEL: use a different model than native for -march flag (see gcc documentation for available models)
  • USE_VLA: activate variable length array support in C, check the compiler support/option flags

Communication:

  • ANNOTATE: enables source code YAML annotation
  • ANNOTATE_LIST: coma separated list of control structure to annotate (For by default)
  • ANNOTATE_LEVEL: level of recursivity for annotations
  • ANNOTATE_INDEPTH_LIST: coma separated white list of control structure to recursively annotate (For by default)

Reference

Brice Videau, Kevin Pouget, Luigi Genovese, Thierry Deutsch, Dimitri Komatitsch, Frédéric Desprez, Jean-François Méhaut. BOAST: A metaprogramming framework to produce portable and efficient computing kernels for HPC applications. International Journal of High Performance Computing Applications, SAGE Publications, 2018, 32 (1), pp.28-44.

Acknowledgment

The research leading to these results has received funding from the European Community's Seventh Framework Programme [FP7/2007-2013] under grant agreement n° 288777 and 610402.