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The Hetrogeneous Habanero-C (HC) language under development in the Habanero project at Rice University provides and implementation of the Habanero execution model for modern heterogeneous (CPU + GPU) architectures.

Table of Contents

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 to Habaneromakes it easier to write new programs and port existing programs with little effort.
  2. Two stage compilation to target targets both domain experts as well as ninja parallel programmers. 
  3. Shared Virtual Memory (SVM) to target rescursive  supports rescursive pointer data structures on GPUthe GPU. 
  4. Meta datalayout framework to generate target 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 hardware underlying platform to support OpenCL. The H2C compiler uses a machine description file given by a Machine Description(MDes) file provided by an user or automatically generated by an auto-tuner and generates tuner to generate a target specific executable.

A short summary of the H2C language H2C framework is included below.  Details 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 or Vivek Sarkar.

 

H2C Language Summary

 The language constructs are classified into communication and computation constructs.

Constructs for Communication 

Heterogeneous Habanero-

C extends

C extends the

Habanero 

Habanero async

, forasync and finish

constructs to target modern heterogeneous architectures.

 The

The async construct, async, is used to asynchronously transfer the data among multiple devices.

Execution of the async statement returns immediately, i.e., the parent task can proceed to its following statement without waiting for the child task to complete.  The

One can easily overlap computation with the asynchronous data transfers. The finish statement, finish <stmt>,

 performs a join operation that causes the parent task to execute <stmt> and then wait until all the tasks created within <stmt> have terminated (including transitively spawned tasks).  The Habanero-C runtime uses a work-stealing scheduler that supports work-first and help-first policies along with places for locality
  • Habanero-C uses phasers for synchronization. Phasers are programming constructs that unify collective and point-to-point synchronization in task parallel programming. Phasers are designed for ease of use and safety, helping programmer productivity in task parallel programming and debugging. The use of phasers guarantees two safety properties: deadlock-freedom and phase-ordering. These properties, along with the generality of its use for dynamic parallelism, distinguish phasers from other synchronization constructs such as barriers, counting semaphores and X10 clocks. In Habanero-C tasks can register on a phaser in on of the 3 modes: SIGNAL_WAIT_MODE, SIGNAL_ONLY_MODE, WAIT_ONLY_MODE.

  • For locality, Habanero-C uses Hierarchical Place Trees(HPTs). HPTs abstract the underlying hardware using hierarchical trees, allowing the program to spawn tasks at places, which for example could be cores, groups of cores sharing cache, nodes, groups of nodes, or other devices such as GPUs or FPGAs. The work-stealing runtime takes advantage of the hardware hierarchy to preserve locality when executing tasks.

     

    • ensures all the data transfers within <stmt> have completed.

     async  [copyin (var1, var2,

    H2C Language Summary

    Constructs for Communication

     async [(place)] [IN (var1, var2, ...)] [COPYIN (var1, var2, 
    ...)] [
    COPYOUT 
    copyout (var1, var2, ...)] [
    AT
    at (dev1, dev2, ...)] [
    PARTITION 
    parition (ratio)];

    - Asynchronously start a new task to execute Stmt in parallel with the parent. A destination place can optionally be specified for where the task should execute. The place can be obtained from the runtime using HC runtime functions (see HPT).

    - Any local variable declared in an outer scope that is used in the async has to be specified in an IN (for variables read by the async), OUT(for variables written by the async), or INOUT(for variables both read and written by the async) clauses. The IN/OUT/OUT clauses have copy-in/copy-out semantics for local variables; selected variables are copied in from the parent scope at the start of the async, and out into the parent scope at the end of the async task.

    - an AWAIT clause can optionally be specified, listing all the data-driven futures (DDF's) that the task should wait on before starting its execution.

    - a phased clause can optionally be specified, registering the async on all the phasers specified in the list (ph1, ph2, ...), or on all the phasers of the parent (if the list is not specified).

    finish Stmt

     - execute Stmt, but wait until all (transitively) spawned asyncs in Stmt's scope have terminated before advancing to the next statement.
    • copyin clause is use to specify the

    Constructs for Computation

      forasync   [in (var1, var2, ...)] [point (ind1, ind2, ...)] [size (siz1, siz2, ...)] [seq (seq1, seq2, ...)] Body

    -- The semantics of the in clause is the same as in the async case.

    -- Loop indices in each dimension are specified by the point clause.

    -- The number of iterations in each dimension is specified by the size clause.

    -- The tile size is specified by the seq clause.

    forasync is lowered and implemented for CPUs in two different ways as follows.

    • 1) Chunked Scheduling: Loop iterations are chunked into blocks of lengths specified by the seq clause.(Default option)
    • 2) Recursive Scheduling: Loop iterations are recursively partitioned until the size of a block size specified by the seq clause is reached. This is similar to the TBB style. (use '-hcc:recursive' option when compiling your program)

    forasync targets heterogeneous platforms by automatically generating host code and OpenCL device code.

    Note: The semantics of forasync does not include a barrier. An explicit finish must  enclose the forasync to synchronize all the iterations.

      

     

     H2C Compiler and Runtime Framework

    H2C uses a two-step compilation. 

     

     

    Overall H2C compilation Framework

     

    Current H2C limitations

    There are some limitations and pitfalls in the current implementation of the HC 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) Pointers to stack variables (including stack-allocated arrays) cannot be reused across "suspendable" points. A suspendable function is a function that can directly or indirectly call a function containing an async statement or a finish statement. A suspendable point is an async statement, the end of a finish statement, or a call to a suspendable function.

    Work-around: copy these stack variables to the heap. There is no limitation on the reuse of heap pointers across suspendable points.

    2) Pointers to HC functions (functions that contain HC constructs or call other HC functions) are not supported in HC.

    Work-around: only use pointers to C functions.

    3) const modifiers are not supported for function parameters or local variables in HC programs.

    Work-around: remove these 'const' modifiers. The semantics of a correct program will remain unchanged, since the only purpose of the 'const' modifiers is to enforce additional compiler checking.

    4) The number of tasks registered on a phaser cannot be larger than the number of worker threads specified with the -nproc option when an HC program is invoked. Otherwise, a deadlock may occur.

    5) HC function calls must be in canonical form; either being a statement or being the right hand-side of an assignment.

    Code Block
    languagecpp
    titleCanonicalized HC function usage
    foo();
b = foo();
a = b + c; // 'foo' value must first be assigned to a variable

    Acknowledgement

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

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