9 citations · 20 across the 6 of their papers we have counts for
4 papers · 1 filter
Microscaling Data Formats for Deep Learning
Bita Darvish Rouhani, Ritchie Zhao, Ankit More +30
Narrow bit-width data formats are key to reducing the computational and storage costs of modern deep learning applications. This paper evaluates Microscaling (MX) data formats that…
SPARTA: Spatial Acceleration for Efficient and Scalable Horizontal Diffusion Weather Stencil Computation
Gagandeep Singh, Alireza Khodamoradi, Kristof Denolf +6
Fast and accurate climate simulations and weather predictions are critical for understanding and preparing for the impact of climate change. Real-world weather and climate modeling…
CHARM: Composing Heterogeneous Accelerators for Matrix Multiply on Versal ACAP Architecture
Jinming Zhuang, Jason Lau, Hanchen Ye +10
Dense matrix multiply (MM) serves as one of the most heavily used kernels in deep learning applications. To cope with the high computation demands of these applications, heterogene…
Tailor: Altering Skip Connections for Resource-Efficient Inference
Olivia Weng, Gabriel Marcano, Vladimir Loncar +7
Deep neural networks use skip connections to improve training convergence. However, these skip connections are costly in hardware, requiring extra buffers and increasing on- and of…