Heterogeneous Habanero-C

Overview

The Heterogeneous Habanero-C (H2C) language, compiler and runtime framework is specifically desgined to achieve portability, productivity and performance on modern heterogeneous (CPU+ GPU) architectures. The main goal is take a machine indpendent program written in H2C and generate a machine specific executable. Some highlights of H2C include:

1. Minimal intuitive language extensions makes it easier to write new programs and port existing programs with little effort.
2. Two stage compilation targets both domain experts as well as ninja parallel programmers. 
3. Shared Virtual Memory (SVM) supports rescursive pointer data structures on the GPU. 
4. Meta datalayout framework generates a target specific data layout.
5. Embedded DSLs for stencils and re-use patterns take advantage of local scratchpad buffers.

H2C requires the underlying platform to support OpenCL. The H2C compiler uses a Machine Description(MDes) file provided by an user or automatically generated by an auto-tuner to generate a target specific executable. H2C uses an offload model wherein the CPU is the host and both CPU and GPU are devices.

A short summary of the H2C framework is included below. Details on the underlying implementation technologies can be found in the Habanero publications web page. The H2C implementation is still evolving at an early stage. If you would like to try out H2C, please contact one of the following people: Deepak Majeti, or Vivek Sarkar.

H2C Language Summary

 The language constructs are classified into communication, computation and synchronization constructs.

Communication Constructs

The async construct, is used to asynchronously transfer the data among multiple devices. One can easily overlap computation with the asynchronous data transfers. The finish statement, finish <stmt>, ensures all the data transfers within <stmt> have completed.

 async  [copyin (var1, var2, ...)] [copyout (var1, var2, ...)] [at (dev1, dev2, ...)] [partition (ratio)];

• copyin clause is used to specify the data that needs to be copied to the device from the host

• copyout clause is used to specify the data that needs to be copied to the host from the device

• at clause is used to specify the target devices

• partition clause is used to specify the ratio of partition

Computation Constructs

The forasync construct is a data/task parallel loop. It is the programmer's responsibility to ensure that loop iterations are independent.

  forasync   [in (var1, var2, ...)] [point (ind1, ind2, ...)] [range (siz1, siz2, ...)] [seq (seq1, seq2, ...)][scratchpad (var1, var2, ...)][at (dev1, dev2, ...)] [partition (ratio)]{Body}

• point clause is used to specify the loop indices in each dimension

• range clause is used to specify the number of iterations in each dimension

• seq clause is used to specify the tile size or the work-group size

• Body represents the loop iteration

Synchronization Constructs

The finish construct ensures all the tasks spawned inside it are completed.

H2C Compiler and Runtime Framework

Two Phase Compilation 

 In the first phase, H2C compiler compiles down a H2C program to a C program, OpenCL kernel and the corresponding host program. Parallelism experts can optionally choose to add optimized OpenCL kernels. The compiler uses a Machine Description(MDes) file to generate a target specific OpenCL kernel and communication. The MDes file can either be given by the programmer or automatically be generated by an auto-tuner.

In the second phase,  a standard C compiler is used to build an exectuable from the generated intermediate files along with the H2C runtime and OpenCL runtime.

Runtime

The H2C runtime includes a memory manger, scheduler and interfaces with the OpenCL runtime.

Example H2C program

finish{
     async copyin(a,b) at(dev);
     foo(); //asynchronously copy data while executing foo
}
finish{
    forasync in(a,b,c,m,n,p) point(i,j) range(0:m,0:n) seq(4,128) shared(a,b) at(dev){
        float temp =0;
 		for(int k=0;k<p;k++){
           temp += a[i*p+k]*b[k*n+j];
        }
        c[i*n+j] =temp;
   }
}
finish{
     async copyout(c) at(dev);
     bar(); //asynchronously copy data while executing bar
}

Current H2C limitations

There are some limitations and pitfalls in the current implementation of the H2C programming model. These limitations are not inherent to the programming model, but rather are a result of incompleteness in the current compiler or runtime implementation.

1) The forasync construct cannot be nested in the current implementation.

2) There is no compiler check for correctness on the forasync body. Any code pattern not supported on the target device will result in runtime errors. 

3) Pointer arithmetic on arrays which are communicated between CPU and GPU is not supported.

Acknowledgement

Partial support for Heterogeneous Habanero-C was provided through the CDSC program of the National Science Foundation with an award in the 2009 Expedition in Computing Program.