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