ChangeLog 9.4 KB

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  1. # StarPU --- Runtime system for heterogeneous multicore architectures.
  2. #
  3. # Copyright (C) 2009-2012 Université de Bordeaux 1
  4. # Copyright (C) 2010, 2011, 2012 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 1.1.0 (svn revision xxxx)
  17. ==============================================
  18. New features:
  19. * OpenGL interoperability support.
  20. * Capability to store compiled OpenCL kernels on the file system
  21. * Capability to load compiled OpenCL kernels
  22. * Performance models measurements can now be provided explicitly by
  23. applications.
  24. Changes:
  25. * The FxT code can now be used on systems other than Linux.
  26. * The cache of starpu_mpi_insert_task is fixed and thus now enabled by
  27. default.
  28. Small changes:
  29. * STARPU_NCPU should now be used instead of STARPU_NCPUS. STARPU_NCPUS is
  30. still available for compatibility reasons.
  31. StarPU 1.0.0 (svn revision 6306)
  32. ==============================================
  33. The extensions-again release
  34. New features:
  35. * Add SOCL, an OpenCL interface on top of StarPU.
  36. * Add a gcc plugin to extend the C interface with pragmas which allows to
  37. easily define codelets and issue tasks.
  38. * Add reduction mode to starpu_mpi_insert_task.
  39. * A new multi-format interface permits to use different binary formats
  40. on CPUs & GPUs, the conversion functions being provided by the
  41. application and called by StarPU as needed (and as less as
  42. possible).
  43. * Deprecate cost_model, and introduce cost_function, which is provided
  44. with the whole task structure, the target arch and implementation
  45. number.
  46. * Permit the application to provide its own size base for performance
  47. models.
  48. * Applications can provide several implementations of a codelet for the
  49. same architecture.
  50. * Add a StarPU-Top feedback and steering interface.
  51. * Permit to specify MPI tags for more efficient starpu_mpi_insert_task
  52. Changes:
  53. * Fix several memory leaks and race conditions
  54. * Make environment variables take precedence over the configuration
  55. passed to starpu_init()
  56. * Libtool interface versioning has been included in libraries names
  57. (libstarpu-1.0.so, libstarpumpi-1.0.so,
  58. libstarpufft-1.0.so, libsocl-1.0.so)
  59. * Install headers under $includedir/starpu/1.0.
  60. * Make where field for struct starpu_codelet optional. When unset, its
  61. value will be automatically set based on the availability of the
  62. different XXX_funcs fields of the codelet.
  63. * Define access modes for data handles into starpu_codelet and no longer
  64. in starpu_task. Hence mark (struct starpu_task).buffers as
  65. deprecated, and add (struct starpu_task).handles and (struct
  66. starpu_codelet).modes
  67. * Fields xxx_func of struct starpu_codelet are made deprecated. One
  68. should use fields xxx_funcs instead.
  69. * Some types were renamed for consistency. when using pkg-config libstarpu,
  70. starpu_deprecated_api.h is automatically included (after starpu.h) to
  71. keep compatibility with existing software. Other changes are mentioned
  72. below, compatibility is also preserved for them.
  73. To port code to use new names (this is not mandatory), the
  74. tools/dev/rename.sh script can be used, and pkg-config starpu-1.0 should
  75. be used.
  76. * The communication cost in the heft and dmda scheduling strategies now
  77. take into account the contention brought by the number of GPUs. This
  78. changes the meaning of the beta factor, whose default 1.0 value should
  79. now be good enough in most case.
  80. Small features:
  81. * Allow users to disable asynchronous data transfers between CPUs and
  82. GPUs.
  83. * Update OpenCL driver to enable CPU devices (the environment variable
  84. STARPU_OPENCL_ON_CPUS must be set to a positive value when
  85. executing an application)
  86. * struct starpu_data_interface_ops --- operations on a data
  87. interface --- define a new function pointer allocate_new_data
  88. which creates a new data interface of the given type based on
  89. an existing handle
  90. * Add a field named magic to struct starpu_task which is set when
  91. initialising the task. starpu_task_submit will fail if the
  92. field does not have the right value. This will hence avoid
  93. submitting tasks which have not been properly initialised.
  94. * Add a hook function pre_exec_hook in struct starpu_sched_policy.
  95. The function is meant to be called in drivers. Schedulers
  96. can use it to be notified when a task is about being computed.
  97. * Add codelet execution time statistics plot.
  98. * Add bus speed in starpu_machine_display.
  99. * Add a STARPU_DATA_ACQUIRE_CB which permits to inline the code to be
  100. done.
  101. * Add gdb functions.
  102. * Add complex support to LU example.
  103. * Permit to use the same data several times in write mode in the
  104. parameters of the same task.
  105. Small changes:
  106. * Increase default value for STARPU_MAXCPUS -- Maximum number of
  107. CPUs supported -- to 64.
  108. * Add man pages for some of the tools
  109. * Add C++ application example in examples/cpp/
  110. * Add an OpenMP fork-join example.
  111. * Documentation improvement.
  112. StarPU 0.9 (svn revision 3721)
  113. ==============================================
  114. The extensions release
  115. * Provide the STARPU_REDUX data access mode
  116. * Externalize the scheduler API.
  117. * Add theoretical bound computation
  118. * Add the void interface
  119. * Add power consumption optimization
  120. * Add parallel task support
  121. * Add starpu_mpi_insert_task
  122. * Add profiling information interface.
  123. * Add STARPU_LIMIT_GPU_MEM environment variable.
  124. * OpenCL fixes
  125. * MPI fixes
  126. * Improve optimization documentation
  127. * Upgrade to hwloc 1.1 interface
  128. * Add fortran example
  129. * Add mandelbrot OpenCL example
  130. * Add cg example
  131. * Add stencil MPI example
  132. * Initial support for CUDA4
  133. StarPU 0.4 (svn revision 2535)
  134. ==============================================
  135. The API strengthening release
  136. * Major API improvements
  137. - Provide the STARPU_SCRATCH data access mode
  138. - Rework data filter interface
  139. - Rework data interface structure
  140. - A script that automatically renames old functions to accomodate with the new
  141. API is available from https://scm.gforge.inria.fr/svn/starpu/scripts/renaming
  142. (login: anonsvn, password: anonsvn)
  143. * Implement dependencies between task directly (eg. without tags)
  144. * Implicit data-driven task dependencies simplifies the design of
  145. data-parallel algorithms
  146. * Add dynamic profiling capabilities
  147. - Provide per-task feedback
  148. - Provide per-worker feedback
  149. - Provide feedback about memory transfers
  150. * Provide a library to help accelerating MPI applications
  151. * Improve data transfers overhead prediction
  152. - Transparently benchmark buses to generate performance models
  153. - Bind accelerator-controlling threads with respect to NUMA locality
  154. * Improve StarPU's portability
  155. - Add OpenCL support
  156. - Add support for Windows
  157. StarPU 0.2.901 aka 0.3-rc1 (svn revision 1236)
  158. ==============================================
  159. The asynchronous heterogeneous multi-accelerator release
  160. * Many API changes and code cleanups
  161. - Implement starpu_worker_get_id
  162. - Implement starpu_worker_get_name
  163. - Implement starpu_worker_get_type
  164. - Implement starpu_worker_get_count
  165. - Implement starpu_display_codelet_stats
  166. - Implement starpu_data_prefetch_on_node
  167. - Expose the starpu_data_set_wt_mask function
  168. * Support nvidia (heterogeneous) multi-GPU
  169. * Add the data request mechanism
  170. - All data transfers use data requests now
  171. - Implement asynchronous data transfers
  172. - Implement prefetch mechanism
  173. - Chain data requests to support GPU->RAM->GPU transfers
  174. * Make it possible to bypass the scheduler and to assign a task to a specific
  175. worker
  176. * Support restartable tasks to reinstanciate dependencies task graphs
  177. * Improve performance prediction
  178. - Model data transfer overhead
  179. - One model is created for each accelerator
  180. * Support for CUDA's driver API is deprecated
  181. * The STARPU_WORKERS_CUDAID and STARPU_WORKERS_CPUID env. variables make it possible to
  182. specify where to bind the workers
  183. * Use the hwloc library to detect the actual number of cores
  184. StarPU 0.2.0 (svn revision 1013)
  185. ==============================================
  186. The Stabilizing-the-Basics release
  187. * Various API cleanups
  188. * Mac OS X is supported now
  189. * Add dynamic code loading facilities onto Cell's SPUs
  190. * Improve performance analysis/feedback tools
  191. * Application can interact with StarPU tasks
  192. - The application may access/modify data managed by the DSM
  193. - The application may wait for the termination of a (set of) task(s)
  194. * An initial documentation is added
  195. * More examples are supplied
  196. StarPU 0.1.0 (svn revision 794)
  197. ==============================================
  198. First release.
  199. Status:
  200. * Only supports Linux platforms yet
  201. * Supported architectures
  202. - multicore CPUs
  203. - NVIDIA GPUs (with CUDA 2.x)
  204. - experimental Cell/BE support
  205. Changes:
  206. * Scheduling facilities
  207. - run-time selection of the scheduling policy
  208. - basic auto-tuning facilities
  209. * Software-based DSM
  210. - transparent data coherency management
  211. - High-level expressive interface