MarkusPuschel at 17:25, 10 March 2014

2014-03-10T17:25:27Z

← Older revision		Revision as of 19:25, 10 March 2014
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	Many applications in media processing, control, graphics, and other domains require efficient small-scale linear		Many applications in media processing, control, graphics, and other domains require efficient small-scale linear
	algebra computations. However, most existing high performance libraries for linear algebra, such as ATLAS or Intel MKL		algebra computations. However, most existing high performance libraries for linear algebra, such as ATLAS or Intel MKL
	are more geared towards large-scale problems (matrix sizes in the hundreds and larger) and towards specific interfaces (e.g., BLAS). In this paper we present LGen: a program generator for small-scale, basic linear algebra computations. The input to LGen is a fixed-size linear algebra expression; the output is a corresponding C function optionally including intrinsics to efficiently use SIMD vector extensions. LGen ~~generates~~ code using two levels		are more geared towards large-scale problems (matrix sizes in the hundreds and larger) and towards specific interfaces (e.g., BLAS). In this paper we present LGen: a program generator for small-scale, basic linear algebra computations. The input to LGen is a fixed-size linear algebra expression; the output is a corresponding C function optionally including intrinsics to efficiently use SIMD vector extensions. LGen is designed closely after Spiral, generating code using two levels of mathematical domain-specific languages (DSLs). The DSLs are used to perform tiling, loop fusion, and vectorization at a high level of abstraction, before the final code is generated. In addition, search is used to select among alternative generated implementations. We show benchmarks of code generated by Lgen against Intel MKL and IPP as well as against alternative generators, such as the C++ template-based Eigen and the BTO compiler. The achieved speed-up is typically about a factor of two to three.
	of mathematical domain-specific languages (DSLs). The DSLs are used to perform tiling, loop fusion, and vectorization at a high level of abstraction, before the final code is generated. In addition, search is used to select among alternative generated implementations. We show benchmarks of code generated by Lgen against Intel MKL and IPP as well as against alternative generators, such as the C++ template-based Eigen and the BTO compiler. The achieved speed-up is typically about a factor of two to three.

MarkusPuschel: Created page with "'''Spiral for Basic Linear Algebra''', ''by Markus Püschel'' Many applications in media processing, control, graphics, and other domains require efficient small-scale linear al..."

2014-03-10T17:24:53Z

Created page with "'''Spiral for Basic Linear Algebra''', ''by Markus Püschel'' Many applications in media processing, control, graphics, and other domains require efficient small-scale linear al..."

New page

'''Spiral for Basic Linear Algebra''', ''by Markus Püschel''

Many applications in media processing, control, graphics, and other domains require efficient small-scale linear
algebra computations. However, most existing high performance libraries for linear algebra, such as ATLAS or Intel MKL
are more geared towards large-scale problems (matrix sizes in the hundreds and larger) and towards specific interfaces (e.g., BLAS). In this paper we present LGen: a program generator for small-scale, basic linear algebra computations. The input to LGen is a fixed-size linear algebra expression; the output is a corresponding C function optionally including intrinsics to efficiently use SIMD vector extensions. LGen generates code using two levels
of mathematical domain-specific languages (DSLs). The DSLs are used to perform tiling, loop fusion, and vectorization at a high level of abstraction, before the final code is generated. In addition, search is used to select among alternative generated implementations. We show benchmarks of code generated by Lgen against Intel MKL and IPP as well as against alternative generators, such as the C++ template-based Eigen and the BTO compiler. The achieved speed-up is typically about a factor of two to three.

WG211/M13Puschel - Revision history

MarkusPuschel at 17:25, 10 March 2014

MarkusPuschel: Created page with "'''Spiral for Basic Linear Algebra''', ''by Markus Püschel'' Many applications in media processing, control, graphics, and other domains require efficient small-scale linear al..."