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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Merchant, Farhad Maity, Arka Mahadurkar, Mahesh Vatwani, Kapil Munje, Ishan Krishna, Madhava Nalesh, S. Gopalan, Nandhini Raha, Soumyendu Nandy, S.K. Narayan, Ranjani |
| Copyright Year | 2015 |
| Abstract | LU and QR factorizations are the computationally dear part of many applications ranging from large scale simulations (e.g. Computational fluid dynamics) to augmented reality. These factorizations exhibit time complexity of O (n3) and are difficult to accelerate due to presence of bandwidth bound kernels, BLAS-1 or BLAS-2 (level-1 or level-2 Basic Linear Algebra Subprograms) along with compute bound kernels (BLAS-3, level-3 BLAS). On the other hand, Coarse Grained Reconfigurable Architectures (CGRAs) have gained tremendous popularity as accelerators in embedded systems due to their flexibility and ease of use. Provisioning these accelerators in High Performance Computing (HPC) platforms is the research challenge wrestled by the computer scientists. We consider a CGRA environment in which several Compute Elements (CEs) enhanced with Custom Functional Units (CFUs) are interconnected over a Network-on-Chip (NoC). In this paper, we carry out extensive micro-architectural exploration for accelerating core kernels like Matrix Multiplication (MM) (BLAS-3) for LU and QR factorizations. Our 5 different design enhancements lead to the reduction in the latency of BLAS-3 kernels. On a stand-alone CFU, we achieve up to 8x speed-up for MM. A commensurate improvement is observed for MM in a CGRA environment. We achieve better GF LOP S/mm2 compared to recent implementations. |
| Starting Page | 153 |
| Ending Page | 158 |
| File Size | 543239 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781479966585 |
| ISSN | 10639667 |
| DOI | 10.1109/VLSID.2015.31 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2015-01-03 |
| Publisher Place | India |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | parallelism reconfigurable architectures numerical linear algebra computation |
| Content Type | Text |
| Resource Type | Article |
| Subject | Electrical and Electronic Engineering Hardware and Architecture |
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