ChangeLog 5.8 KB

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  1. # StarPU --- Runtime system for heterogeneous multicore architectures.
  2. #
  3. # Copyright (C) 2009, 2010, 2011 Université de Bordeaux 1
  4. # Copyright (C) 2010, 2011 Centre National de la Recherche Scientifique
  5. #
  6. # StarPU is free software; you can redistribute it and/or modify
  7. # it under the terms of the GNU Lesser General Public License as published by
  8. # the Free Software Foundation; either version 2.1 of the License, or (at
  9. # your option) any later version.
  10. #
  11. # StarPU is distributed in the hope that it will be useful, but
  12. # WITHOUT ANY WARRANTY; without even the implied warranty of
  13. # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
  14. #
  15. # See the GNU Lesser General Public License in COPYING.LGPL for more details.
  16. StarPU 1.0 (svn revision xxxx)
  17. ==============================================
  18. The extensions-again release
  19. * Applications can provide several implementations of a codelet for the same
  20. architecture.
  21. * A new multi-format interface permits to use different binary formats on
  22. CPUs & GPUs, the conversion functions being provided by the application and
  23. called by StarPU as needed (and as less as possible).
  24. * Add a gcc plugin to extend the C interface with pragmas which allow to
  25. easily define codelets and issue tasks.
  26. * Add codelet execution time statistics plot.
  27. * Add bus speed in starpu_machine_display.
  28. * Add a StarPU-Top feedback and steering interface.
  29. * Documentation improvement.
  30. * Add a STARPU_DATA_ACQUIRE_CB which permits to inline the code to be done.
  31. * Permit to specify MPI tags for more efficient starpu_mpi_insert_task
  32. * Add a communications.
  33. * Add SOCL, an OpenCL interface on top of StarPU.
  34. * Add gdb functions.
  35. * Add complex support to LU example.
  36. * Add an OpenMP fork-join example.
  37. * Some types were renamed for consistency. The tools/dev/rename.sh script
  38. can be used to port code using former names.
  39. StarPU 0.9 (svn revision 3721)
  40. ==============================================
  41. The extensions release
  42. * Provide the STARPU_REDUX data access mode
  43. * Externalize the scheduler API.
  44. * Add theoretical bound computation
  45. * Add the void interface
  46. * Add power consumption optimization
  47. * Add parallel task support
  48. * Add starpu_mpi_insert_task
  49. * Add profiling information interface.
  50. * Add STARPU_LIMIT_GPU_MEM environment variable.
  51. * OpenCL fixes
  52. * MPI fixes
  53. * Improve optimization documentation
  54. * Upgrade to hwloc 1.1 interface
  55. * Add fortran example
  56. * Add mandelbrot OpenCL example
  57. * Add cg example
  58. * Add stencil MPI example
  59. * Initial support for CUDA4
  60. StarPU 0.4 (svn revision 2535)
  61. ==============================================
  62. The API strengthening release
  63. * Major API improvements
  64. - Provide the STARPU_SCRATCH data access mode
  65. - Rework data filter interface
  66. - Rework data interface structure
  67. - A script that automatically renames old functions to accomodate with the new
  68. API is available from https://scm.gforge.inria.fr/svn/starpu/scripts/renaming
  69. (login: anonsvn, password: anonsvn)
  70. * Implement dependencies between task directly (eg. without tags)
  71. * Implicit data-driven task dependencies simplifies the design of
  72. data-parallel algorithms
  73. * Add dynamic profiling capabilities
  74. - Provide per-task feedback
  75. - Provide per-worker feedback
  76. - Provide feedback about memory transfers
  77. * Provide a library to help accelerating MPI applications
  78. * Improve data transfers overhead prediction
  79. - Transparently benchmark buses to generate performance models
  80. - Bind accelerator-controlling threads with respect to NUMA locality
  81. * Improve StarPU's portability
  82. - Add OpenCL support
  83. - Add support for Windows
  84. StarPU 0.2.901 aka 0.3-rc1 (svn revision 1236)
  85. ==============================================
  86. The asynchronous heterogeneous multi-accelerator release
  87. * Many API changes and code cleanups
  88. - Implement starpu_worker_get_id
  89. - Implement starpu_worker_get_name
  90. - Implement starpu_worker_get_type
  91. - Implement starpu_worker_get_count
  92. - Implement starpu_display_codelet_stats
  93. - Implement starpu_data_prefetch_on_node
  94. - Expose the starpu_data_set_wt_mask function
  95. * Support nvidia (heterogeneous) multi-GPU
  96. * Add the data request mechanism
  97. - All data transfers use data requests now
  98. - Implement asynchronous data transfers
  99. - Implement prefetch mechanism
  100. - Chain data requests to support GPU->RAM->GPU transfers
  101. * Make it possible to bypass the scheduler and to assign a task to a specific
  102. worker
  103. * Support restartable tasks to reinstanciate dependencies task graphs
  104. * Improve performance prediction
  105. - Model data transfer overhead
  106. - One model is created for each accelerator
  107. * Support for CUDA's driver API is deprecated
  108. * The STARPU_WORKERS_CUDAID and STARPU_WORKERS_CPUID env. variables make it possible to
  109. specify where to bind the workers
  110. * Use the hwloc library to detect the actual number of cores
  111. StarPU 0.2.0 (svn revision 1013)
  112. ==============================================
  113. The Stabilizing-the-Basics release
  114. * Various API cleanups
  115. * Mac OS X is supported now
  116. * Add dynamic code loading facilities onto Cell's SPUs
  117. * Improve performance analysis/feedback tools
  118. * Application can interact with StarPU tasks
  119. - The application may access/modify data managed by the DSM
  120. - The application may wait for the termination of a (set of) task(s)
  121. * An initial documentation is added
  122. * More examples are supplied
  123. StarPU 0.1.0 (svn revision 794)
  124. ==============================================
  125. First release.
  126. Status:
  127. * Only supports Linux platforms yet
  128. * Supported architectures
  129. - multicore CPUs
  130. - NVIDIA GPUs (with CUDA 2.x)
  131. - experimental Cell/BE support
  132. Changes:
  133. * Scheduling facilities
  134. - run-time selection of the scheduling policy
  135. - basic auto-tuning facilities
  136. * Software-based DSM
  137. - transparent data coherency management
  138. - High-level expressive interface