PUMA publications for /tag/unithttps://puma.ub.uni-stuttgart.de/tag/unitPUMA RSS feed for /tag/unit2024-03-29T16:08:11+01:00Sparse matrix vector multiplications on graphic processorshttps://puma.ub.uni-stuttgart.de/bibtex/2ce0df7291d15f3b0f1467222f3958c4d/amerwafaiamerwafai2016-01-29T09:34:55+01:00CUDA Graphics myown SCOPE Architecture HLRS Device Compute GPU Unit Processing Unified <meta content="thesis" itemprop="educationalUse"/><span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Mhd. Amer Wafai" itemprop="url" href="/person/1782fe775e19c904f41d1b5e185f207f1/author/0"><span itemprop="name">M. Wafai</span></a></span></span>. </span><span class="additional-entrytype-information"><em>University of Stuttgart, </em><em>Nobelstr. 19, 70569, Stuttgart, </em>(<em><span>November 2009<meta content="November 2009" itemprop="datePublished"/></span></em>)</span>Fri Jan 29 09:34:55 CET 2016Nobelstr. 19, 70569, Stuttgart11Sparse matrix vector multiplications on graphic processors2009CUDA Graphics myown SCOPE Architecture HLRS Device Compute GPU Unit Processing Unified The modern computer architecture is moving towards multi-core systems. Intel processors are now coming with double or even quad cores like Xeon processor. Graphics Processing Units (GPUs) are considered to be highly parallel multi-core processors with tremendous performance. They are specially designed to deal with 3D and realtime graphics. And after the introduction of the new API, Compute Unified Device Architecture (CUDA), from NVIDA, the GPU became an attractive choice for general purpose parallel computing to solve many complex numerical problems.
Sparse Matrix-Vector (SpMV) multiplication is one of the most important kernels in scientific computing. Its sparsity, irregularity and indirect addressing properties present new challenges to map it to multi-core systems.
The objective of this work is to analyze the speed of execution of SpMV multiplication on NVIDIA GPUs (Tesla C1060). An algorithm based on a tailored version of ELLPACK, called Aligned-ELLPACK-R, as well as different algorithms have been developed using different storage formats. These implementations are done using the programming language CUDA. Finally the comparison of that performance has been done with respect to different implementations of SpMV on Intel Xeon E5560 processor using Jagged Diagonal Formats (JAD), ELLPACK and ELLPACK-R storage formats.
The results show the superiority of JAD storage format over the matrices used to test SpMV on conventional super scaler processors. SpMV on Tesla C1060 based on Aligned-ELLPACK-R outperforms the fastest implementation on CPU with speedup factor 13 times. It also outperforms the CUDA library based on ELLPACK with 2.3 speedup factor.Soft_XR – Soft Robotic Explorer Unithttps://puma.ub.uni-stuttgart.de/bibtex/253563f59d2a196336ef9eb70e91036c7/itkeitke2020-05-22T14:22:38+02:00biomat dahy 2018 soft_xr unit itke from:petraheim petrs sippach explorer robotic <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Timo Sippach" itemprop="url" href="/person/13f659b408627ef2ea292b4b8776caec2/author/0"><span itemprop="name">T. Sippach</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Jan Petrs" itemprop="url" href="/person/13f659b408627ef2ea292b4b8776caec2/author/1"><span itemprop="name">J. Petrs</span></a></span>, </span> and <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Hanaa Dahy" itemprop="url" href="/person/13f659b408627ef2ea292b4b8776caec2/author/2"><span itemprop="name">H. Dahy</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/Book" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="name">Proceedings of the 1st Conference of Design Computing 2018</span>, </em></span><em>Prague, Czech Republique, </em>(<em><span>201ß<meta content="201ß" itemprop="datePublished"/></span></em>)</span>Fri May 22 14:22:38 CEST 2020Prague, Czech RepubliqueProceedings of the 1st Conference of Design Computing 2018Soft_XR – Soft Robotic Explorer Unit201ßbiomat dahy 2018 soft_xr unit itke from:petraheim petrs sippach explorer robotic Soft_XR – Soft Robotic Explorer Unithttps://puma.ub.uni-stuttgart.de/bibtex/253563f59d2a196336ef9eb70e91036c7/petraheimpetraheim2020-05-20T13:12:39+02:00biomat dahy soft_xr petrs robotic 2018 unit itke sippach explorer <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Timo Sippach" itemprop="url" href="/person/13f659b408627ef2ea292b4b8776caec2/author/0"><span itemprop="name">T. Sippach</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Jan Petrs" itemprop="url" href="/person/13f659b408627ef2ea292b4b8776caec2/author/1"><span itemprop="name">J. Petrs</span></a></span>, </span> and <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Hanaa Dahy" itemprop="url" href="/person/13f659b408627ef2ea292b4b8776caec2/author/2"><span itemprop="name">H. Dahy</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/Book" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="name">Proceedings of the 1st Conference of Design Computing 2018</span>, </em></span><em>Prague, Czech Republique, </em>(<em><span>201ß<meta content="201ß" itemprop="datePublished"/></span></em>)</span>Wed May 20 13:12:39 CEST 2020Prague, Czech RepubliqueProceedings of the 1st Conference of Design Computing 2018Soft_XR – Soft Robotic Explorer Unit201ßbiomat dahy soft_xr petrs robotic 2018 unit itke sippach explorer New Approach in Thermal Monitoring of Large Power Transformers Applied on a 350 MVA ODAF–Cooled Unithttps://puma.ub.uni-stuttgart.de/bibtex/2d810c9a4b4782d6fdb37e29a549a0007/annettegugelannettegugel2020-08-10T13:55:45+02:00Monitoring Large MVA Transformers ODAF–Cooled Unit Applied 350 Thermal Power <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Enzo Cardillo" itemprop="url" href="/person/17694a309dcdcdb89e56ca770c55dbfe4/author/0"><span itemprop="name">E. Cardillo</span></a></span>, </span> and <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Kurt Feser" itemprop="url" href="/person/17694a309dcdcdb89e56ca770c55dbfe4/author/1"><span itemprop="name">K. Feser</span></a></span></span>. </span><span class="additional-entrytype-information">(<em><span>2004<meta content="2004" itemprop="datePublished"/></span></em>)</span>Mon Aug 10 13:55:45 CEST 2020New Approach in Thermal Monitoring of Large Power Transformers Applied on a 350 MVA ODAF–Cooled Unit2004Monitoring Large MVA Transformers ODAF–Cooled Unit Applied 350 Thermal Power