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COMP Superscalar Framework ChangeLog
Release number: 1.1.1
Release date: 1-Oct-2013
-------------------------------
This is the first public release of the COMP Superscalar Framework.
Release number: 1.1.2
Release date: 5-Jun-2014
-------------------------------
* C/C++ binding.
* Python binding.
* Integrated Development Environment for COMPSs applications (IDE)
* Priority tasks.
* New tracing system using the Extrae tool.
* Deleting a file within an OE removes all the replicas in the system.
* Updated the SSH Trilead adaptor libraries to remove unnecessary sleeps.
* Scripts for submission to queue systems (LSF, PBS, Slurm).
* Configuration of application directory and library path in project XML file.
* Separate logs for resubmitted / rescheduled tasks.
* Create a COMPSs sandbox in the workers instead of JavaGAT's.
Release number: 1.2
Release date: Nov-2014
-------------------------------
* N implementations for task methods, each with its own constraints.
* Constraint-aware resource management.
* Support for multicore tasks.
* Pluggable schedulers: facilitate the addition of new schedulers and policies.
* Extended support for objects in C/C++ binding.
* Extended IDE for N implementations and deployment through PMES.
* Update cloud connector for rOCCI to work with rocci-cli v4.2.5.
* Enhance rOCCI connector to compute the real VM creation times.
* Extended resources schema to support Virtual Appliances pricing.
* New LSF GAT adaptor.
* Deprecated Azure and EMOTIVE Cloud connectors.
* Deprecated Azure GAT adaptor.
Release number: 1.3
Release date: Nov-2015
-------------------------------
New features:
* Runtime:
- Persistent workers: workers can be deployed on computing nodes and persist during all the application lifetime, reducing runtime overhead.
Previous implementation of workers based on a per task process is still supported.
- Enhanced logging system
- Interoperable communication layer: different inter-nodes communication protocol is supported by implementing the Adaptor interface (JavaGAT
and NIO implementations already included)
- Simplified cloud connectors interface
- JClouds connector
* Python:
- Added constraints support
- Enhanced methods support
- Lists accepted as a tasks' parameter type
- Support for user decorators
* Tools:
- New monitoring tool: with new views, as workload and possibility of visualizing information about previous runs
- Enhanced Tracing mechanism
* Simplified execution scripts
* Simplified installation on Supercomputers
Known Limitations:
* Exceptions raised from tasks are not handled by the master
* Java tasks must be declared as public
* Java objects MUST be serializable or, at least, follow the java beans model
* Support limited to SOAP based services
* Persistent Workers do NOT isolate task executions in a sandbox
For further information please refer to COMPSs User Manual: Application development
Release number: 1.4
Release date: April-2016
-------------------------------
New features:
* Runtime:
- Support for Dockers added
- Support for Chameleon added
- Object cache for persistent workers
- Improved error management
- Connector for submitting tasks to MN supercomputer from external COMPSs applications added
- Bug-fixes
* Python:
- Bug-fixes
* Tools:
- Enhanced Tracing mechanism:
· Reduced overhead using native java API
· Support for communications instrumentation added
· Support for PAPI hardware counters added
Known Limitations:
* When executing python applications with constraints in the cloud the initial VMs
must be set to 0
For further information please refer to COMPSs User Manual: Application development
Release number: 2.0 Amapola (Poppy)
Release date: November-2016
-------------------------------
New features:
* Runtime:
- Upgrade to Java 8
- Support to remote input files (input files already at workers)
- Integration with Persistent Objects
- Elasticity with Docker and Mesos
- Multi-processor support (CPUs, GPUs, FPGAs)
- Dynamic constraints with environment variables
- Scheduling taking into account the full tasks graph (not only ready tasks)
- Support for SLURM clusters
- Initial COMPSs/OmpSs integration
- Replicated tasks: Tasks executed in all the workers
- Explicit Barrier
* Python:
- Python user events and HW counters tracing
- Improved PyCOMPSs serialization. Added support for lambda and generator parameters.
* C:
- Constraints support
* Tools:
- Improved current graph visualization on COMPSs Monitor
Improvements:
- Simplified Resource and Project files (NO retrocompatibility)
- Improved binding workers execution (use pipes instead of Java Process Builders)
- Simplifies cluster job scripts and supercomputers configuration
- Several bug fixes
Known Limitations:
* When executing python applications with constraints in the cloud the initial VMs
must be set to 0
For further information please refer to COMPSs User Manual: Application development
Release number: 2.1 Bougainvillea
Release date: June-2017
-------------------------------
New features:
* Runtime:
- New annotations to simplify tasks that call external binaries
- Integration with other programming models (MPI, OmpSs,..)
- Support for Singularity containers in Clusters
- Extension of the scheduling to support multi-node tasks (MPI apps as tasks)
- Support for Grid Engine job scheduler in clusters
- Language flag automatically inferred in runcompss script
- New schedulers based on tasks’ generation order
- Core affinity and over-subscribing thread management in multi-core cluster queue scripts (used with MKL libraries, for example)
* Python:
- @local annotation to support simpler data synchronizations in master (requires to install guppy)
- Support for args and kwargs parameters as task dependencies
- Task versioning support in Python (multiple behaviors of the same task)
- New Python persistent workers that reduce overhead of Python tasks
- Support for task-thread affinity
- Tracing extended to support for Python user events and HW counters (with known issues)
* C:
- Extension of file management API (compss_fopen, compss_ifstream, compss_ofstream, compss_delete_file)
- Support for task-thread affinity
* Tools:
- Visualization of not-running tasks in current graph of the COMPSs Monitor
Improvements:
- Improved PyCOMPSs serialization
- Improvements in cluster job scripts and supercomputers configuration
- Several bug fixes
Known Limitations:
- When executing Python applications with constraints in the cloud the <InitialVMs> property must be set to 0
- Tasks that invoke Numpy and MKL may experience issues if tasks use a different number of MKL threads. This is due to
the fact that MKL reuses threads in the different calls and it does not change the number of threads from one call to another.
For further information, please refer to “COMPSs User Manual: Application development guide”.
Release number: 2.2 Camellia
Release date: November-2017
-------------------------------
New features:
* Runtime:
- Support Elasticity in SLURM-managed clusters
- Support for Elasticity with Singularity containers
- Integration of Decaf flows as COMPSs tasks
- Changed integratedtoolkit packages by es.bsc.compss (requires changes in Java application codes)
* Python:
- Support for Decaf applications as tasks
- External decorators (MPI, Binary, Decaf, etc.) extended with streams and prefixes support
- Added support for applications that use the argparse library
- Added support for dictionary unrolling on task call
* C:
- Persistent worker in C-binding (enabled with persistent_worker_c=true)
- Inter-task object cache
- Support for object methods as tasks
- Added support applications with threads in master code
Improvements:
- Integration with Jupyter-notebook improved
- Improved cleanup - Unused files removal
- Several bug fixes
Known Limitations:
- Tasks that invoke Numpy and MKL may experience issues if tasks use a different number of MKL threads. This is due to
the fact that MKL reuses threads in the different calls and it does not change the number of threads from one call to another.
For further information, please refer to “COMPSs User Manual: Application development guide”.
Release number: 2.3 Daisy
Release date: June-2018
-------------------------------
New features:
* Runtime:
- Persistent storage API implementation based on Redis (distributed as default implementation with COMPSs)
- Support for FPGA constraints and reconfiguration scripts
- Support for PBS Job Scheduler and the Archer Supercomputer
* Java:
- New API call to delete objects in order to reduce application memory usage
* Python:
- Support for Python 3
- Support for Python virtual environments (venv)
- Support for running PyCOMPSs as a Python module
- Support for tasks returning multiple elements (returns=#)
- Automatic import of dummy PyCOMPSs API
* C:
- Persistent worker with Memory-to-memory transfers
- Support for arrays (no serialization required)
Improvements:
- Distribution with docker images
- Support for sharing objects in memory between tasks (no file serialization is required now with persistent workers)
- Source Code and example applications distribution on Github
- Automatic inference of task return
- Improved obsolete object cleanup
- Improved tracing support for applications using persistent memory
- Improved finalization process to reduce zombie processes
- Several bug fixes
Known Limitations:
- Tasks that invoke Numpy and MKL may experience issues if a different MKL threads count is used in different tasks. This is due to the fact that MKL reuses threads in the different calls and it does not change the number of threads from one call to another.
For further information, please refer to “COMPSs User Manual: Application development guide”.