Get our free extension to see links to code for papers anywhere online!

Add to Chrome

Add to Firefox

Get Pro 💎 Log In/Sign Up 🚀

Picture for Sanchit Misra

Sanchit Misra

https://www.catalyzex.com

Accelerating Barnes-Hut t-SNE Algorithm by Efficient Parallelization on Multi-Core CPUs

Dec 22, 2022
Narendra Chaudhary, Alexander Pivovar, Pavel Yakovlev, Andrey Gorshkov, Sanchit Misra

Figure 1 for Accelerating Barnes-Hut t-SNE Algorithm by Efficient Parallelization on Multi-Core CPUs

Figure 2 for Accelerating Barnes-Hut t-SNE Algorithm by Efficient Parallelization on Multi-Core CPUs

Figure 3 for Accelerating Barnes-Hut t-SNE Algorithm by Efficient Parallelization on Multi-Core CPUs

Figure 4 for Accelerating Barnes-Hut t-SNE Algorithm by Efficient Parallelization on Multi-Core CPUs

Access Paper or Ask Questions

DistGNN-MB: Distributed Large-Scale Graph Neural Network Training on x86 via Minibatch Sampling

Nov 11, 2022
Md Vasimuddin, Ramanarayan Mohanty, Sanchit Misra, Sasikanth Avancha

Figure 1 for DistGNN-MB: Distributed Large-Scale Graph Neural Network Training on x86 via Minibatch Sampling

Figure 2 for DistGNN-MB: Distributed Large-Scale Graph Neural Network Training on x86 via Minibatch Sampling

Figure 3 for DistGNN-MB: Distributed Large-Scale Graph Neural Network Training on x86 via Minibatch Sampling

Figure 4 for DistGNN-MB: Distributed Large-Scale Graph Neural Network Training on x86 via Minibatch Sampling

Access Paper or Ask Questions

DistGNN: Scalable Distributed Training for Large-Scale Graph Neural Networks

Apr 16, 2021
Vasimuddin Md, Sanchit Misra, Guixiang Ma, Ramanarayan Mohanty, Evangelos Georganas, Alexander Heinecke, Dhiraj Kalamkar, Nesreen K. Ahmed, Sasikanth Avancha

Figure 1 for DistGNN: Scalable Distributed Training for Large-Scale Graph Neural Networks

Figure 2 for DistGNN: Scalable Distributed Training for Large-Scale Graph Neural Networks

Figure 3 for DistGNN: Scalable Distributed Training for Large-Scale Graph Neural Networks

Figure 4 for DistGNN: Scalable Distributed Training for Large-Scale Graph Neural Networks

Access Paper or Ask Questions

Efficient and Generic 1D Dilated Convolution Layer for Deep Learning

Apr 16, 2021
Narendra Chaudhary, Sanchit Misra, Dhiraj Kalamkar, Alexander Heinecke, Evangelos Georganas, Barukh Ziv, Menachem Adelman, Bharat Kaul

Figure 1 for Efficient and Generic 1D Dilated Convolution Layer for Deep Learning

Figure 2 for Efficient and Generic 1D Dilated Convolution Layer for Deep Learning

Figure 3 for Efficient and Generic 1D Dilated Convolution Layer for Deep Learning

Figure 4 for Efficient and Generic 1D Dilated Convolution Layer for Deep Learning

Access Paper or Ask Questions

Tensor Processing Primitives: A Programming Abstraction for Efficiency and Portability in Deep Learning Workloads

Apr 14, 2021
Evangelos Georganas, Dhiraj Kalamkar, Sasikanth Avancha, Menachem Adelman, Cristina Anderson, Alexander Breuer, Narendra Chaudhary, Abhisek Kundu, Vasimuddin Md, Sanchit Misra, Ramanarayan Mohanty, Hans Pabst, Barukh Ziv, Alexander Heinecke

Figure 1 for Tensor Processing Primitives: A Programming Abstraction for Efficiency and Portability in Deep Learning Workloads

Figure 2 for Tensor Processing Primitives: A Programming Abstraction for Efficiency and Portability in Deep Learning Workloads

Figure 3 for Tensor Processing Primitives: A Programming Abstraction for Efficiency and Portability in Deep Learning Workloads

Figure 4 for Tensor Processing Primitives: A Programming Abstraction for Efficiency and Portability in Deep Learning Workloads

Access Paper or Ask Questions

Deep Graph Library Optimizations for Intel(R) x86 Architecture

Jul 13, 2020
Sasikanth Avancha, Vasimuddin Md, Sanchit Misra, Ramanarayan Mohanty

Figure 1 for Deep Graph Library Optimizations for Intel(R) x86 Architecture

Figure 2 for Deep Graph Library Optimizations for Intel(R) x86 Architecture

Figure 3 for Deep Graph Library Optimizations for Intel(R) x86 Architecture

Figure 4 for Deep Graph Library Optimizations for Intel(R) x86 Architecture

Access Paper or Ask Questions

LISA: Towards Learned DNA Sequence Search

Oct 10, 2019
Darryl Ho, Jialin Ding, Sanchit Misra, Nesime Tatbul, Vikram Nathan, Vasimuddin Md, Tim Kraska

Figure 1 for LISA: Towards Learned DNA Sequence Search

Figure 2 for LISA: Towards Learned DNA Sequence Search

Figure 3 for LISA: Towards Learned DNA Sequence Search

Figure 4 for LISA: Towards Learned DNA Sequence Search

Access Paper or Ask Questions

Log in or sign up instantly 🚀

🔥 Discover incredible developments in machine intelligence

🤖 Quickly get code for any ML model

🔑 Get help from authors, engineers & researchers

Continue with email

Continue with Google

Continue with Github

Continue with LinkedIn

Continue with Facebook

Continue with Twitter

Seconds away from lift-off 🚀

To ensure authors get your request, sign in to proceed instantly

Continue with email

Continue with Github

Continue with Twitter

Continue with Google

Continue with LinkedIn

Continue with Facebook

© 2023 CatalyzeX

Follow us