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AMD Announces AMD Core Math Library (ACML) 4.0 with Enhanced Optimizations for Third-Generation AMD Opteron(TM) Processors
SUNNYVALE, Calif. --(Business Wire)-- AMD (NYSE: AMD) today announced significant updates to its AMD Core Math Library (ACML) designed to provide software developers with highly optimized, multi-threaded math routines used by scientific, engineering, business and consumer applications that require maximum performance. Designed for developers and mathematical programmers seeking additional support for multi-threading and complex high performance computing projects, ACML offers support for all major x86 operating environments including Windows(R), Linux(R), and Solaris. ACML can be downloaded at no charge from AMD Developer Central, an on-line destination for developers seeking support for multi-threading software development projects or x86-based computing projects that demand highly-optimized code.
"The enhancements in ACML 4.0 underscore AMD's ongoing commitment to delivering more advanced and powerful development tools to programmers, especially as the industry continues to evolve to many-core processing environments," said Margaret Lewis, director of Commercial Solutions, AMD. "With these enhancements to ACML, programmers seeking to unleash the computing power of AMD's native quad-core processors will have highly optimized support for complex mathematical and linear programming."
ACML is a set of numerical routines tuned specifically for AMD64 processors designed to increase support for linear programming, an optimizing technique for mathematically intensive code, in multi-core processing environments. Enhancements to ACML announced today include an update to the Linear Algebra Package (LAPACK) and increased optimizations for Quad-Core AMD Processors, including Quad-Core AMD Opteron(TM) Processors and the upcoming AMD Phenom(TM) quad-core processor. ACML is specifically designed to use key components of next-generation AMD processors, including Streaming SIMD Extensions (SSE), and to create highly threaded code that can help developers to better utilize multi-core processor technology. ACML consists of the following features:
-- A full implementation of Level 1, 2 and 3 Basic Linear Algebra Subroutines (BLAS), with key routines optimized for high performance on AMD Opteron processors.
-- A full suite of Linear Algebra (LAPACK) routines. As well as taking advantage of the highly-tuned BLAS kernels, a key set of LAPACK routines has been further optimized to achieve considerably higher performance than standard LAPACK implementations.
-- A comprehensive suite of Fast Fourier Transforms (FFTs) in single-, double-, single-complex and double-complex data types.
-- Fast scalar, vector, and array math transcendental library routines optimized for high performance on AMD Opteron processors.
-- Random Number Generators in both single- and double-precision.
ACML is designed to be used with a variety of popular x86 C/C++ and Fortran compilers, including GCC and GFortran (The GNU Compiler Collection), PGI, Pathscale, Sun, and Intel, providing developers with freedom of choice when creating highly-optimized, multi-threaded code. With the tuned implementations of industry-standard math libraries and other frequently used scientific subroutines, ACML enables developers to accelerate complex programming efforts such as weather modeling, finite element analysis, computational fluid dynamics, financial analysis, and oil and gas applications.
ACML Partner Support
"Over the past four years, PathScale has collaborated with AMD and it's technology partner NAG to deliver a custom version of ACML compiled with the PathScale compiler," said Duncan Poole, Director, PathScale. "The PathScale Compiler Suite version 3.1 will be used to compile a unique version of ACML incorporating tuning for AMD's native quad-core so that PathScale customers may do whole program optimization when using ACML, and leverage our outstanding OpenMP support. Together we provide excellent performance on AMD processors and reduced development time."
"PGI has been including ACML with its cross-platform products since PGI Release 5.0 back in June of 2003," said Douglas Miles, director, The Portland Group. "ACML is a high quality library that delivers first rate performance on x64 processors generally and AMD64 processors in particular. PGI customers place great value in having a library of highly-tuned BLAS, LAPACK and FFT routines freely available with the PGI compilers and tools."
"We welcome AMD's commitment to the Solaris platform with its latest release of ACML", said Don Kretsch, Sr. Director in Sun Developer Tools. "In combination with the optimizing compilers and tools in Sun Studio software, this library allows developers to create high performance applications on AMD Opteron processor-based systems, running the Solaris operating system."
First made available in 2003 to deliver an enhanced development tool and provide developers with a core set of AMD64 mathematical functions, ACML was launched in collaboration with the Numerical Algorithms Group (NAG). Over the past four years, AMD has evolved ACML to assist with today's most complex mathematical problems. ACML is being used by a growing community of ISVs, corporate developers, and solution providers who are creating optimized software specifically for AMD multi-core processor technology.
For more information about the AMD Core Math Library (ACML) or to download ACML 4.0 at no charge, please visit http://developer.amd.com.
About AMD
Advanced Micro Devices (NYSE: AMD) is a leading global provider of innovative processing solutions in the computing, graphics and consumer electronics markets. AMD is dedicated to driving open innovation, choice and industry growth by delivering superior customer-centric solutions that empower consumers and businesses worldwide. For more information, visit www.amd.com.
AMD, the AMD Arrow logo, AMD Opteron, and combinations thereof are trademarks of Advanced Micro Devices, Inc. Other names are for informational purposes only and may be trademarks of their respective owners.
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