{
"item_title" : "Optimization of SVD over GPGPU using OpenCL",
"item_author" : [" Nadeem Akhtar", "Shazeb Nawaz Khan "],
"item_description" : "Many of the engineering applications require linear algebra to furnish the analysis. Singular Value Decomposition is one of the most powerful tool of linear algebra. This method alone serves many computational and analytical purposes. Although the computation of SVD of a matrix is bulky, the process involves a sequence of vector operations. This makes it a good candidate for parallelization of over Graphic Processors. This book proposes parallelization of SVD modules in LAPACK over GPGPU using OpenCL, which is platform independent and focuses on routines beyond BLAS.",
"item_img_path" : "https://covers1.booksamillion.com/covers/bam/3/65/940/089/3659400890_b.jpg",
"price_data" : {
"retail_price" : "59.29", "online_price" : "59.29", "our_price" : "59.29", "club_price" : "59.29", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : ""
}
}
Overview
Many of the engineering applications require linear algebra to furnish the analysis. Singular Value Decomposition is one of the most powerful tool of linear algebra. This method alone serves many computational and analytical purposes. Although the computation of SVD of a matrix is bulky, the process involves a sequence of vector operations. This makes it a good candidate for parallelization of over Graphic Processors. This book proposes parallelization of SVD modules in LAPACK over GPGPU using OpenCL, which is platform independent and focuses on routines beyond BLAS.
This item is Non-Returnable
Customers Also Bought
Details
- ISBN-13: 9783659400896
- ISBN-10: 3659400890
- Publisher: LAP Lambert Academic Publishing
- Publish Date: June 2013
- Dimensions: 9 x 6 x 0.22 inches
- Shipping Weight: 0.32 pounds
- Page Count: 92
Related Categories
