54 citations · 173 across the 13 of their papers we have counts for
12 papers · 1 filter
Accelerating Neural Network Inference with Processing-in-DRAM: From the Edge to the Cloud
Geraldo F. Oliveira, Juan Gómez-Luna, Saugata Ghose +2
Neural networks (NNs) are growing in importance and complexity. A neural network's performance (and energy efficiency) can be bound either by computation or memory resources. The p…
Heterogeneous Data-Centric Architectures for Modern Data-Intensive Applications: Case Studies in Machine Learning and Databases
Geraldo F. Oliveira, Amirali Boroumand, Saugata Ghose +2
Today's computing systems require moving data back-and-forth between computing resources (e.g., CPUs, GPUs, accelerators) and off-chip main memory so that computation can take plac…
Enabling High-Performance and Energy-Efficient Hybrid Transactional/Analytical Databases with Hardware/Software Cooperation
Amirali Boroumand, Saugata Ghose, Geraldo F. Oliveira +1
A growth in data volume, combined with increasing demand for real-time analysis (using the most recent data), has resulted in the emergence of database systems that concurrently su…
Extending Memory Capacity in Consumer Devices with Emerging Non-Volatile Memory: An Experimental Study
Geraldo F. Oliveira, Saugata Ghose, Juan Gómez-Luna +8
The number and diversity of consumer devices are growing rapidly, alongside their target applications' memory consumption. Unfortunately, DRAM scalability is becoming a limiting fa…
Google Neural Network Models for Edge Devices: Analyzing and Mitigating Machine Learning Inference Bottlenecks
Amirali Boroumand, Saugata Ghose, Berkin Akin +5
Emerging edge computing platforms often contain machine learning (ML) accelerators that can accelerate inference for a wide range of neural network (NN) models. These models are de…
Polynesia: Enabling Effective Hybrid Transactional/Analytical Databases with Specialized Hardware/Software Co-Design
Amirali Boroumand, Saugata Ghose, Geraldo F. Oliveira +1
An exponential growth in data volume, combined with increasing demand for real-time analysis (i.e., using the most recent data), has resulted in the emergence of database systems t…
Mitigating Edge Machine Learning Inference Bottlenecks: An Empirical Study on Accelerating Google Edge Models
Amirali Boroumand, Saugata Ghose, Berkin Akin +5
As the need for edge computing grows, many modern consumer devices now contain edge machine learning (ML) accelerators that can compute a wide range of neural network (NN) models w…
GenASM: A High-Performance, Low-Power Approximate String Matching Acceleration Framework for Genome Sequence Analysis
Damla Senol Cali, Gurpreet S. Kalsi, Zülal Bingöl +13
Genome sequence analysis has enabled significant advancements in medical and scientific areas such as personalized medicine, outbreak tracing, and the understanding of evolution. U…
Enabling the Adoption of Processing-in-Memory: Challenges, Mechanisms, Future Research Directions
Saugata Ghose, Kevin Hsieh, Amirali Boroumand +2
Poor DRAM technology scaling over the course of many years has caused DRAM-based main memory to increasingly become a larger system bottleneck. A major reason for the bottleneck is…
Using ECC DRAM to Adaptively Increase Memory Capacity
Yixin Luo, Saugata Ghose, Tianshi Li +5
Modern DRAM modules are often equipped with hardware error correction capabilities, especially for DRAM deployed in large-scale data centers, as process technology scaling has incr…
LazyPIM: Efficient Support for Cache Coherence in Processing-in-Memory Architectures
Amirali Boroumand, Saugata Ghose, Minesh Patel +7
Processing-in-memory (PIM) architectures have seen an increase in popularity recently, as the high internal bandwidth available within 3D-stacked memory provides greater incentive…
Buddy-RAM: Improving the Performance and Efficiency of Bulk Bitwise Operations Using DRAM
Vivek Seshadri, Donghyuk Lee, Thomas Mullins +7
Bitwise operations are an important component of modern day programming. Many widely-used data structures (e.g., bitmap indices in databases) rely on fast bitwise operations on lar…