56 citations · 64 across the 12 of their papers we have counts for
12 papers
Mitigating Catastrophic Forgetting in Long Short-Term Memory Networks
Ketaki Joshi, Raghavendra Pradyumna Pothukuchi, Andre Wibisono +1
Continual learning on sequential data is critical for many machine learning (ML) deployments. Unfortunately, LSTM networks, which are commonly used to learn on sequential data, suf…
A Multi-Site Accelerator-Rich Processing Fabric for Scalable Brain-Computer Interfacing
Karthik Sriram, Raghavendra Pradyumna Pothukuchi, Michał Gerasimiuk +5
Hull is an accelerator-rich distributed implantable Brain-Computer Interface (BCI) that reads biological neurons at data rates that are 2-3 orders of magnitude higher than the prio…
Distill: Domain-Specific Compilation for Cognitive Models
Jan Vesely, Raghavendra Pradyumna Pothukuchi, Ketaki Joshi +3
This paper discusses our proposal and implementation of Distill, a domain-specific compilation tool based on LLVM to accelerate cognitive models. Cognitive models explain the proce…
MIND: In-Network Memory Management for Disaggregated Data Centers
Seung-seob Lee, Yanpeng Yu, Yupeng Tang +3
Memory-compute disaggregation promises transparent elasticity, high utilization and balanced usage for resources in data centers by physically separating memory and compute into ne…
Efficient Kernel Object Management for Tiered Memory Systems with KLOC
Sudarsun Kannan, Yujie Ren, Abhishek Bhatacharjee
Software-controlled heterogeneous memory systems have the potential to improve performance, efficiency, and cost tradeoffs in emerging systems. Delivering on this promise requires…
SPARTA: A Divide and Conquer Approach to Address Translation for Accelerators
Javier Picorel, Seyed Alireza Sanaee Kohroudi, Zi Yan +3
Virtual memory (VM) is critical to the usability and programmability of hardware accelerators. Unfortunately, implementing accelerator VM efficiently is challenging because the are…