|
All the software tools included with Intel Cluster Toolkit have undergone a major revision to give you the best parallel performance analysis tools for cluster software development.
The following list contains just a few of the many new features included in this latest version.
|
Intel® MPI Library 3.1
- Multiple usability improvements
- Simplified variable names, options, and diagnostics
- Unified Intel memory management support (i_malloc)
- PVFS and PANFS file system support
- Lightweight statistics gathering
- Enhanced documentation
- Improved application performance
- Improved default performance settings
- Automated performance tuning on Linux
- Intelligent process layout and pinning
- Scalable application startup/termination
- Event driven mode for the shared memory and socket transfers
- Extended interoperability
- Support for Windows Computer Cluster Server and Red Hat Enterprise Linux 5.0
- Intel® 10.1 C++ and Fortran compiler support
- TotalView* and IDB process attachment support
|
Intel® Trace Analyzer and Collector 7.1
- Multiple usability improvements
- More reports, more graphics, more analysis, more filtering, more powerful!
- MPI Correctness Checking
 Check MPI parameters, data types, buffers, communicators, messages, and collective operations
Detect deadlocks and corruption
- Command line integration to Trace Analyzer
- Automatic instrumentation of user binaries for all supported platforms and OS
- Distributed memory checking, advanced data handling (large and aggregated data)
- Improved performance
- Accelerated data caching to reduce runtime overhead and memory consumption
- Lightweight statistics gathering
- Optimized stack unwinding for linking trace information back to source code
- Extended interoperability
- Thread safe tracing with extended tracing support for Cluster OpenMP*, Global Arrays (GA), and non-MPI applications
- Support for Microsoft Windows* (XP, Server 2003, and Compute Cluster Server)
- Compatible with Microsoft and Intel compilers and Visual Studio*
- Support for MPI-1, SHMEM, MPI-IO, and ROMIO
- Automatic compiler-driven instrumentation with Intel and GNU compilers
|
Intel® Math Kernel Library 10.0
- New functions
- Sparse BLAS zero-based indexing and support for real data
- PARDISO/DSS (Parallel Direct Sparse Solver) support for Out-of-core (OOC) memory
- Iterative Sparse Solver support extended with ILUT preconditioner, Sparse 0-based indexing, and new mkl_scsrgemv function
- Vector Math arithmetic functions (Mul, Conj, MulbyConj, CIS, Abs)
- Multiple usability improvements
- Greatly enhanced User’s Guide
- New user callable threading functions allowing greater control
- Extended Java support with many examples in documentation
- Improved application performance
- Multi-core multithreading optimization
- New Vector Math “Enhanced Performance” accuracy mode
- Faster FFTs DftiCommitDescriptor function which allocates less memory
- Numerous optimizations for small BLAS/LAPACK/FFT problem sizes
- Extended interoperability
- Cluster enabled capability available in single MKL product
- New layered architecture to better support Microsoft and GCC compiler threading
- Debian and Ubuntu support
- Improved support for multiple compiler environments, threading libraries, and interfaces through restructuring of the library files
|
Intel® MPI Benchmarks 3.1
- Multiple usability improvements
- New benchmarks (Gather(v), Scatter(v))
- Improved application performance
- New Command line flags to control cache reuse and to limit memory usage
- Options for cold cache operation mode, maximum buffer size setting and dynamic iteration count determination
- Run time improvements for collectives like Alltoall(v) on large clusters
- Extended interoperability
- Support for Windows Compute Cluster Server
|
|
|
|
Print
