15 papers
MAFIA: Machine Learning Acceleration on FPGAs for IoT Applications
Nikhil Pratap Ghanathe, Vivek Seshadri, Rahul Sharma +2
Recent breakthroughs in ML have produced new classes of models that allow ML inference to run directly on milliwatt-powered IoT devices. On one hand, existing ML-to-FPGA compilers…
Multilingual and code-switching ASR challenges for low resource Indian languages
Anuj Diwan, Rakesh Vaideeswaran, Sanket Shah +19
Recently, there is increasing interest in multilingual automatic speech recognition (ASR) where a speech recognition system caters to multiple low resource languages by taking adva…
The Virtual Block Interface: A Flexible Alternative to the Conventional Virtual Memory Framework
Nastaran Hajinazar, Pratyush Patel, Minesh Patel +7
Computers continue to diversify with respect to system designs, emerging memory technologies, and application memory demands. Unfortunately, continually adapting the conventional v…
In-DRAM Bulk Bitwise Execution Engine
Vivek Seshadri, Onur Mutlu
Many applications heavily use bitwise operations on large bitvectors as part of their computation. In existing systems, performing such bulk bitwise operations requires the process…
Dataplant: Enhancing System Security with Low-Cost In-DRAM Value Generation Primitives
Lois Orosa, Yaohua Wang, Ivan Puddu +13
DRAM manufacturers have been prioritizing memory capacity, yield, and bandwidth for years, while trying to keep the design complexity as simple as possible. DRAM chips do not carry…
PipeDream: Fast and Efficient Pipeline Parallel DNN Training
Aaron Harlap, Deepak Narayanan, Amar Phanishayee +4
PipeDream is a Deep Neural Network(DNN) training system for GPUs that parallelizes computation by pipelining execution across multiple machines. Its pipeline parallel computing mod…