starpu-max/ChangeLog

# StarPU --- Runtime system for heterogeneous multicore architectures.
#
# Copyright (C) 2009, 2010, 2011  Université de Bordeaux 1
# Copyright (C) 2010, 2011, 2012  Centre National de la Recherche Scientifique
#
# StarPU is free software; you can redistribute it and/or modify
# it under the terms of the GNU Lesser General Public License as published by
# the Free Software Foundation; either version 2.1 of the License, or (at
# your option) any later version.
#
# StarPU is distributed in the hope that it will be useful, but
# WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
#
# See the GNU Lesser General Public License in COPYING.LGPL for more details.

StarPU 1.0 (svn revision xxxx)
==============================================
The extensions-again release

  * Update OpenCL driver to enable CPU devices (the environment variable
	STARPU_OPENCL_ON_CPUS must be set to a positive value when
	executing an application)
  * struct starpu_data_interface_ops --- operations on a data
        interface --- define a new function pointer allocate_new_data
        which creates a new data interface of the given type based on
        an existing handle
  * Make environment variables take precedence over the configuration
        passed to starpu_init()
  * Add man pages for some of the tools
  * Add reduction mode to starpu_mpi_insert_task
  * Add C++ application example in examples/cpp/
  * Increase default value for STARPU_MAXCPUS -- Maximum number of
        CPUs supported -- to 64.
  * Libtool interface versioning has been included in libraries names
        (libstarpu-1.0.so, libstarpumpi-1.0.so,
        libstarpufft-1.0.so, libsocl-1.0.so)
  * Enable by default the SOCL extension.
  * Enable by default the GCC plug-in extension.
  * Add a field named magic to struct starpu_task which is set when
        initialising the task. starpu_task_submit will fail if the
        field does not have the right value. This will hence avoid
        submitting tasks which have not been properly initialised.
  * Make where field for struct starpu_codelet optional. When unset, its
	value will be automatically set based on the availability of the
	different XXX_funcs fields of the codelet.
  * Add a hook function pre_exec_hook in struct starpu_sched_policy.
        The function is meant to be called in drivers. Schedulers
        can use it to be notified when a task is about being computed.
  * Define access modes for data handles into starpu_codelet and no longer
	in starpu_task. Hence mark (struct starpu_task).buffers as
	deprecated, and add (struct starpu_task).handles and (struct
	starpu_codelet).modes
  * Install headers under $includedir/starpu/1.0.
  * Deprecate cost_model, and introduce cost_function, which is provided
	with the whole task structure, the target arch and implementation
	number
  * Permit the application to provide its own size base for performance
	models
  * Fields xxx_func of struct starpu_codelet are made deprecated. One
	should use instead fields xxx_funcs.
  * Applications can provide several implementations of a codelet for the
	same architecture.
  * A new multi-format interface permits to use different binary formats
	on CPUs & GPUs, the conversion functions being provided by the
	application and called by StarPU as needed (and as less as
	possible).
  * Add a gcc plugin to extend the C interface with pragmas which allows to
	easily define codelets and issue tasks.
  * Add codelet execution time statistics plot.
  * Add bus speed in starpu_machine_display.
  * Add a StarPU-Top feedback and steering interface.
  * Documentation improvement.
  * Add a STARPU_DATA_ACQUIRE_CB which permits to inline the code to be
	done.
  * Permit to specify MPI tags for more efficient starpu_mpi_insert_task
  * Add SOCL, an OpenCL interface on top of StarPU.
  * Add gdb functions.
  * Add complex support to LU example.
  * Add an OpenMP fork-join example.
  * Permit to use the same data several times in write mode in the
	parameters of the same task.
  * Some types were renamed for consistency. The tools/dev/rename.sh
	script can be used to port code using former names. You can also
	choose to include starpu_deprecated_api.h (after starpu.h) to keep
	using the old types.

StarPU 0.9 (svn revision 3721)
==============================================
The extensions release

  * Provide the STARPU_REDUX data access mode
  * Externalize the scheduler API.
  * Add theoretical bound computation
  * Add the void interface
  * Add power consumption optimization
  * Add parallel task support
  * Add starpu_mpi_insert_task
  * Add profiling information interface.
  * Add STARPU_LIMIT_GPU_MEM environment variable.
  * OpenCL fixes
  * MPI fixes
  * Improve optimization documentation
  * Upgrade to hwloc 1.1 interface
  * Add fortran example
  * Add mandelbrot OpenCL example
  * Add cg example
  * Add stencil MPI example
  * Initial support for CUDA4

StarPU 0.4 (svn revision 2535)
==============================================
The API strengthening release

  * Major API improvements
    - Provide the STARPU_SCRATCH data access mode
    - Rework data filter interface
    - Rework data interface structure
    - A script that automatically renames old functions to accomodate with the new
      API is available from https://scm.gforge.inria.fr/svn/starpu/scripts/renaming
      (login: anonsvn, password: anonsvn)
  * Implement dependencies between task directly (eg. without tags)
  * Implicit data-driven task dependencies simplifies the design of
    data-parallel algorithms
  * Add dynamic profiling capabilities
    - Provide per-task feedback
    - Provide per-worker feedback
    - Provide feedback about memory transfers
  * Provide a library to help accelerating MPI applications
  * Improve data transfers overhead prediction
    - Transparently benchmark buses to generate performance models
    - Bind accelerator-controlling threads with respect to NUMA locality
  * Improve StarPU's portability
    - Add OpenCL support
    - Add support for Windows

StarPU 0.2.901 aka 0.3-rc1 (svn revision 1236)
==============================================
The asynchronous heterogeneous multi-accelerator release

  * Many API changes and code cleanups
    - Implement starpu_worker_get_id
    - Implement starpu_worker_get_name
    - Implement starpu_worker_get_type
    - Implement starpu_worker_get_count
    - Implement starpu_display_codelet_stats
    - Implement starpu_data_prefetch_on_node
    - Expose the starpu_data_set_wt_mask function
  * Support nvidia (heterogeneous) multi-GPU
  * Add the data request mechanism
    - All data transfers use data requests now
    - Implement asynchronous data transfers
    - Implement prefetch mechanism
    - Chain data requests to support GPU->RAM->GPU transfers
  * Make it possible to bypass the scheduler and to assign a task to a specific
    worker
  * Support restartable tasks to reinstanciate dependencies task graphs
  * Improve performance prediction
    - Model data transfer overhead
    - One model is created for each accelerator
  * Support for CUDA's driver API is deprecated
  * The STARPU_WORKERS_CUDAID and STARPU_WORKERS_CPUID env. variables make it possible to
    specify where to bind the workers
  * Use the hwloc library to detect the actual number of cores

StarPU 0.2.0 (svn revision 1013)
==============================================
The Stabilizing-the-Basics release

  * Various API cleanups
  * Mac OS X is supported now
  * Add dynamic code loading facilities onto Cell's SPUs
  * Improve performance analysis/feedback tools
  * Application can interact with StarPU tasks
    - The application may access/modify data managed by the DSM
    - The application may wait for the termination of a (set of) task(s)
  * An initial documentation is added
  * More examples are supplied


StarPU 0.1.0 (svn revision 794)
==============================================
First release.

Status:
 * Only supports Linux platforms yet
 * Supported architectures
   - multicore CPUs
   - NVIDIA GPUs (with CUDA 2.x)
   - experimental Cell/BE support

Changes:
 * Scheduling facilities
   - run-time selection of the scheduling policy
   - basic auto-tuning facilities
 * Software-based DSM
   - transparent data coherency management
   - High-level expressive interface