Zobrazeno 1 - 10
of 163
pro vyhledávání: '"Rajopadhye, Sanjay"'
Memory bandwidth is known to be a performance bottleneck for FPGA accelerators, especially when they deal with large multi-dimensional data-sets. A large body of work focuses on reducing of off-chip transfers, but few authors try to improve the effic
Externí odkaz:
http://arxiv.org/abs/2401.12071
Optimization pipelines targeting polyhedral programs try to maximize the compute throughput. Traditional approaches favor reuse and temporal locality; while the communicated volume can be low, failure to optimize spatial locality may cause a low I/O
Externí odkaz:
http://arxiv.org/abs/2312.03646
Reductions combine multiple input values with an associative operator to produce a single (or multiple) result(s). When the same input value contributes to multiple outputs, there is an opportunity to reuse partial results, enabling reduction simplif
Externí odkaz:
http://arxiv.org/abs/2309.11826
Programs admitting a polyhedral representation can be transformed in many ways for locality and parallelism, notably loop tiling. Data flow analysis can then compute dependence relations between iterations and between tiles. When tiling is applied, c
Externí odkaz:
http://arxiv.org/abs/2211.15933
Autor:
Bhattarai, Manish, Kharat, Namita, Skau, Erik, Nebgen, Benjamin, Djidjev, Hristo, Rajopadhye, Sanjay, Smith, James P., Alexandrov, Boian
With the boom in the development of computer hardware and software, social media, IoT platforms, and communications, there has been an exponential growth in the volume of data produced around the world. Among these data, relational datasets are growi
Externí odkaz:
http://arxiv.org/abs/2202.09512
Offloading compute-intensive kernels to hardware accelerators relies on the large degree of parallelism offered by these platforms. However, the effective bandwidth of the memory interface often causes a bottleneck, hindering the accelerator's effect
Externí odkaz:
http://arxiv.org/abs/2202.05933
Autor:
Rajopadhye, Sanjay
\emph{Reductions} combine collections of input values with an associative (and usually also commutative) operator to produce either a single, or a collection of outputs. They are ubiquitous in computing, especially with big data and deep learning. Wh
Externí odkaz:
http://arxiv.org/abs/2010.03074
Autor:
Bora, Utpal, Das, Santanu, Kukreja, Pankaj, Joshi, Saurabh, Upadrasta, Ramakrishna, Rajopadhye, Sanjay
In the era of Exascale computing, writing efficient parallel programs is indispensable and at the same time, writing sound parallel programs is very difficult. Specifying parallelism with frameworks such as OpenMP is relatively easy, but data races i
Externí odkaz:
http://arxiv.org/abs/1912.12189
Autor:
Bhattarai, Manish, kharat, Namita, Boureima, Ismael, Skau, Erik, Nebgen, Benjamin, Djidjev, Hristo, Rajopadhye, Sanjay, Smith, James P., Alexandrov, Boian
Publikováno v:
In Journal of Parallel and Distributed Computing September 2023 179
RNA-RNA interaction (RRI) is ubiquitous and has complex roles in the cellular functions. In human health studies, miRNA-target and lncRNAs are among an elite class of RRIs that have been extensively studied. Bacterial ncRNA-target and RNA interferenc
Externí odkaz:
http://arxiv.org/abs/1904.01235