starpu-max/ChangeLog

# StarPU --- Runtime system for heterogeneous multicore architectures.
#
# Copyright (C) 2009-2013  Université de Bordeaux 1
# Copyright (C) 2010, 2011, 2012, 2013  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 1.2.0 (svn revision xxxx)
==============================================

New features:

StarPU 1.1.0 (svn revision xxxx)
==============================================

New features:
  * OpenGL interoperability support.
  * Capability to store compiled OpenCL kernels on the file system
  * Capability to load compiled OpenCL kernels
  * Performance models measurements can now be provided explicitly by
    applications.
  * Capability to emit communication statistics when running MPI code
  * Add starpu_unregister_submit, starpu_data_acquire_on_node and
    starpu_data_invalidate_submit
  * New functionnality to wrapper starpu_insert_task to pass a array of
	data_handles via the parameter STARPU_DATA_ARRAY
  * Enable GPU-GPU direct transfers.
  * GCC plug-in
	- Add `registered' attribute
	- A new pass was added that warns about the use of possibly
	  unregistered memory buffers.
  * SOCL
        - Manual mapping of commands on specific devices is now
	  possible
        - SOCL does not require StarPU CPU tasks anymore. CPU workers
          are automatically disabled to enhance performance of OpenCL
          CPU devices
  * New interface: COO matrix.
  * Data interfaces: The pack operation of user-defined data interface
    defines a new parameter count which should be set to the size of
    the buffer created by the packing of the data.
  * MPI:
        - Communication statistics for MPI can only be enabled at
	  execution time by defining the environment variable
	  STARPU_COMM_STATS
        - Communication cache mechanism is enabled by default, and can
	  only be disabled at execution time by setting the
	  environment variable STARPU_MPI_CACHE to 0.
        - Initialisation functions starpu_mpi_initialize_extended()
  	  and starpu_mpi_initialize() have been made deprecated. One
	  should now use starpu_mpi_init(int *, char ***, int). The
	  last parameter indicates if MPI should be initialised.
        - Collective detached operations have new parameters, a
	  callback function and a argument. This is to be consistent
	  with the detached point-to-point communications.
        - When exchanging user-defined data interfaces, the size of
	  the data is the size returned by the pack operation, i.e
	  data with dynamic size can now be exchanged with StarPU-MPI.
        - New functionality starpu_mpi_irecv_probe_detached which
  	  first tests if the message is available before calling MPI_Recv.
  * Add experimental simgrid support, to simulate execution with various
    number of CPUs, GPUs, amount of memory, etc.
  * Add support for OpenCL simulators (which provide simulated execution time)
  * Add support for Temanejo, a task graph debugger
  * Theoretical bound lp output now includes data transfer time.
  * Update OpenCL driver to only enable CPU devices (the environment
        variable STARPU_OPENCL_ONLY_ON_CPUS must be set to a positive
	value when executing an application)
  * Add Scheduling contexts to separate computation resources
    	- Scheduling policies take into account the set of resources corresponding
	to the context it belongs to
	- Add support to dynamically change scheduling contexts
	(Create and Delete a context, Add Workers to a context, Remove workers from a context)
	- Add support to indicate to which contexts the tasks are submitted
  * Add the Hypervisor to manage the Scheduling Contexts automatically
    	- The Contexts can be registered to the Hypervisor
	- Only the registered contexts are managed by the Hypervisor
	- The Hypervisor can detect the initial distribution of resources of 
	a context and constructs it consequently (the cost of execution is required)
    	- Several policies can adapt dynamically the distribution of resources
	in contexts if the initial one was not appropriate
	- Add a platform to implement new policies of redistribution
	of resources
  * Implement a memory manager which checks the global amount of
    memory available on devices, and checks there is enough memory
    before doing an allocation on the device.
  * Discard environment variable STARPU_LIMIT_GPU_MEM and define
    instead STARPU_LIMIT_CUDA_MEM and STARPU_LIMIT_OPENCL_MEM
  * Introduce new variables STARPU_LIMIT_CUDA_devid_MEM and
    STARPU_LIMIT_OPENCL_devid_MEM to limit memory per specific device
  * Introduce new variable STARPU_LIMIT_CPU_MEM to limit memory for
    the CPU devices
  * New function starpu_malloc_flags to define a memory allocation with
    constraints based on the following values:
    - STARPU_MALLOC_PINNED specifies memory should be pinned
    - STARPU_MALLOC_COUNT specifies the memory allocation should be in
      the limits defined by the environment variables STARPU_LIMIT_xxx
      (see above). When no memory is left, starpu_malloc_flag tries
      to reclaim memory from StarPU and returns -ENOMEM on failure.
  * starpu_malloc calls starpu_malloc_flags with a value of flag set
    to STARPU_MALLOC_PINNED
  * Define new function starpu_free_flags similarly to starpu_malloc_flags

Small features:
  * Add starpu_worker_get_by_type and starpu_worker_get_by_devid
  * Add starpu_fxt_stop_profiling/starpu_fxt_start_profiling which permits to
    pause trace recording.
  * Add trace_buffer_size configuration field to permit to specify the tracing
    buffer size.
  * Add starpu_codelet_profile and starpu_codelet_histo_profile, tools which draw
    the profile of a codelet.
  * File STARPU-REVISION --- containing the SVN revision number from which
    StarPU was compiled --- is installed in the share/doc/starpu directory
  * starpu_perfmodel_plot can now directly draw GFlops curves.
  * New configure option --enable-mpi-progression-hook to enable the
    activity polling method for StarPU-MPI.
  * Permit to disable sequential consistency for a given task.

Changes:
  * Fix the block filter functions.
  * Fix StarPU-MPI on Darwin.
  * The FxT code can now be used on systems other than Linux.
  * Keep only one hashtable implementation common/uthash.h
  * The cache of starpu_mpi_insert_task is fixed and thus now enabled by
    default.
  * Improve starpu_machine_display output.
  * Standardize objects name in the performance model API
  * SOCL
    - Virtual SOCL device has been removed
    - Automatic scheduling still available with command queues not
      assigned to any device
    - Remove modified OpenCL headers. ICD is now the only supported
      way to use SOCL.
    - SOCL test suite is only run when environment variable
      SOCL_OCL_LIB_OPENCL is defined. It should contain the location
      of the libOpenCL.so file of the OCL ICD implementation.
  * Fix main memory leak on multiple unregister/re-register.
  * Improve hwloc detection by configure
  * Cell:
    - It is no longer possible to enable the cell support via the
      gordon driver
    - Data interfaces no longer define functions to copy to and from
      SPU devices
    - Codelet no longer define pointer for Gordon implementations
    - Gordon workers are no longer enabled
    - Gordon performance models are no longer enabled
  * Fix data transfer arrows in paje traces
  * The "heft" scheduler no longer exists. Users should now pick "dmda"
    instead.
  * StarPU can now use poti to generate paje traces.
  * Rename scheduling policy "parallel greedy" to "parallel eager"
  * Rename all filter functions to follow the pattern
    starpu_DATATYPE_filter_FILTERTYPE. The script
    tools/dev/rename_filter.sh is provided to rename your existing
    applications using filters.
  * Rename function starpu_helper_cublas_init to starpu_cublas_init
  * Rename function starpu_helper_cublas_shutdown to starpu_cublas_shutdown
  * Rename function starpu_allocate_buffer_on_node to starpu_malloc_on_node
  * Rename function starpu_free_buffer_on_node to starpu_free_on_node

Small changes:
  * STARPU_NCPU should now be used instead of STARPU_NCPUS. STARPU_NCPUS is
	still available for compatibility reasons.
  * include/starpu.h includes all include/starpu_*.h files, applications
	therefore only need to have #include <starpu.h>
  * Active task wait is now included in blocked time.
  * Fix GCC plugin linking issues starting with GCC 4.7.
  * Fix forcing calibration of never-calibrated archs.
  * CUDA applications are no longer compiled with the "-arch sm_13"
    option. It is specifically added to applications which need it.

StarPU 1.0.3 (svn revision 7379)
==============================================

Changes:
  * Several bug fixes in the build system
  * Bug fixes in source code for non-Linux systems
  * Fix generating FXT traces bigger than 64MiB.
  * Improve ENODEV error detections in StarPU FFT

StarPU 1.0.2 (svn revision xxx)
==============================================

Changes:
  * Add starpu_block_shadow_filter_func_vector and an example.
  * Add tag dependency in trace-generated DAG.
  * Fix CPU binding for optimized CPU-GPU transfers.
  * Fix parallel tasks CPU binding and combined worker generation.
  * Fix generating FXT traces bigger than 64MiB.

StarPU 1.0.1 (svn revision 6659)
==============================================

Changes:
  * hwloc support. Warn users when hwloc is not found on the system and
	produce error when not explicitely disabled.
  * Several bug fixes
  * GCC plug-in
	- Add `#pragma starpu release'
	- Fix bug when using `acquire' pragma with function parameters
	- Slightly improve test suite coverage
	- Relax the GCC version check
  * Update SOCL to use new API
  * Documentation improvement.

StarPU 1.0.0 (svn revision 6306)
==============================================
The extensions-again release

New features:
  * Add SOCL, an OpenCL interface on top of StarPU.
  * Add a gcc plugin to extend the C interface with pragmas which allows to
	easily define codelets and issue tasks.
  * Add reduction mode to starpu_mpi_insert_task.
  * 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).
  * 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.
  * Applications can provide several implementations of a codelet for the
	same architecture.
  * Add a StarPU-Top feedback and steering interface.
  * Permit to specify MPI tags for more efficient starpu_mpi_insert_task

Changes:
  * Fix several memory leaks and race conditions
  * Make environment variables take precedence over the configuration
        passed to starpu_init()
  * 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)
  * Install headers under $includedir/starpu/1.0.
  * 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.
  * 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
  * Fields xxx_func of struct starpu_codelet are made deprecated. One
	should use fields xxx_funcs instead.
  * Some types were renamed for consistency. when using pkg-config libstarpu,
        starpu_deprecated_api.h is automatically included (after starpu.h) to
        keep compatibility with existing software. Other changes are mentioned
        below, compatibility is also preserved for them.
        To port code to use new names (this is not mandatory), the
        tools/dev/rename.sh script can be used, and pkg-config starpu-1.0 should
        be used.
  * The communication cost in the heft and dmda scheduling strategies now
        take into account the contention brought by the number of GPUs. This
        changes the meaning of the beta factor, whose default 1.0 value should
        now be good enough in most case.

Small features:
  * Allow users to disable asynchronous data transfers between CPUs and
	GPUs.
  * 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
  * 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.
  * 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.
  * Add codelet execution time statistics plot.
  * Add bus speed in starpu_machine_display.
  * Add a STARPU_DATA_ACQUIRE_CB which permits to inline the code to be
	done.
  * Add gdb functions.
  * Add complex support to LU example.
  * Permit to use the same data several times in write mode in the
	parameters of the same task.

Small changes:
  * Increase default value for STARPU_MAXCPUS -- Maximum number of
        CPUs supported -- to 64.
  * Add man pages for some of the tools
  * Add C++ application example in examples/cpp/
  * Add an OpenMP fork-join example.
  * Documentation improvement.


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


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