Optimization techniques for GPU programming
In the past decade, Graphics Processing Units have played an important role in the field of
high-performance computing and they still advance new fields such as IoT, autonomous …
high-performance computing and they still advance new fields such as IoT, autonomous …
[PDF][PDF] The Chinese Wall Security Policy.
DFC Brewer, MJ Nash - S&P, 1989 - facweb.iitkgp.ac.in
Everyone who has seen the movie Wall Street will have seen a commercial security policy in
action. The recent work of Clark and Wilson and the WIPCIS initiative (the Workshop on …
action. The recent work of Clark and Wilson and the WIPCIS initiative (the Workshop on …
Auto-tuning a high-level language targeted to GPU codes
Determining the best set of optimizations to apply to a kernel to be executed on the graphics
processing unit (GPU) is a challenging problem. There are large sets of possible …
processing unit (GPU) is a challenging problem. There are large sets of possible …
CSR5: An efficient storage format for cross-platform sparse matrix-vector multiplication
W Liu, B Vinter - Proceedings of the 29th ACM on International …, 2015 - dl.acm.org
Sparse matrix-vector multiplication (SpMV) is a fundamental building block for numerous
applications. In this paper, we propose CSR5 (Compressed Sparse Row 5), a new storage …
applications. In this paper, we propose CSR5 (Compressed Sparse Row 5), a new storage …
GPU-accelerated preconditioned iterative linear solvers
This work is an overview of our preliminary experience in develo** a high-performance
iterative linear solver accelerated by GPU coprocessors. Our goal is to illustrate the …
iterative linear solver accelerated by GPU coprocessors. Our goal is to illustrate the …
Efficient sparse matrix-vector multiplication on x86-based many-core processors
Sparse matrix-vector multiplication (SpMV) is an important kernel in many scientific
applications and is known to be memory bandwidth limited. On modern processors with …
applications and is known to be memory bandwidth limited. On modern processors with …
A unified sparse matrix data format for efficient general sparse matrix-vector multiplication on modern processors with wide SIMD units
Sparse matrix-vector multiplication (spMVM) is the most time-consuming kernel in many
numerical algorithms and has been studied extensively on all modern processor and …
numerical algorithms and has been studied extensively on all modern processor and …
Efficient sparse matrix-vector multiplication on GPUs using the CSR storage format
JL Greathouse, M Daga - SC'14: Proceedings of the …, 2014 - ieeexplore.ieee.org
The performance of sparse matrix vector multiplication (SpMV) is important to computational
scientists. Compressed sparse row (CSR) is the most frequently used format to store sparse …
scientists. Compressed sparse row (CSR) is the most frequently used format to store sparse …
A quantitative performance analysis model for GPU architectures
Y Zhang, JD Owens - 2011 IEEE 17th international symposium …, 2011 - ieeexplore.ieee.org
We develop a microbenchmark-based performance model for NVIDIA GeForce 200-series
GPUs. Our model identifies GPU program bottlenecks and quantitatively analyzes …
GPUs. Our model identifies GPU program bottlenecks and quantitatively analyzes …
Sparsep: Towards efficient sparse matrix vector multiplication on real processing-in-memory architectures
Several manufacturers have already started to commercialize near-bank Processing-In-
Memory (PIM) architectures, after decades of research efforts. Near-bank PIM architectures …
Memory (PIM) architectures, after decades of research efforts. Near-bank PIM architectures …