9 citations · 19 across the 8 of their papers we have counts for
6 papers · 1 filter
Presto: Hardware Acceleration of Ciphers for Hybrid Homomorphic Encryption
Yeonsoo Jeon, Mattan Erez, Michael Orshansky
Hybrid Homomorphic Encryption (HHE) combines symmetric key and homomorphic encryption to reduce ciphertext expansion crucial in client-server deployments of HE. Special symmetric c…
Reducing Load Latency with Cache Level Prediction
Majid Jalili, Mattan Erez
High load latency that results from deep cache hierarchies and relatively slow main memory is an important limiter of single-thread performance. Data prefetch helps reduce this lat…
Accelerating Bandwidth-Bound Deep Learning Inference with Main-Memory Accelerators
Benjamin Y. Cho, Jeageun Jung, Mattan Erez
DL inference queries play an important role in diverse internet services and a large fraction of datacenter cycles are spent on processing DL inference queries. Specifically, the m…
WoLFRaM: Enhancing Wear-Leveling and Fault Tolerance in Resistive Memories using Programmable Address Decoders
Leonid Yavits, Lois Orosa, Suyash Mahar +4
Resistive memories have limited lifetime caused by limited write endurance and highly non-uniform write access patterns. Two main techniques to mitigate endurance-related memory fa…
Near Data Acceleration with Concurrent Host Access
Benjamin Y. Cho, Yongkee Kwon, Sangkug Lym +1
Near-data accelerators (NDAs) that are integrated with main memory have the potential for significant power and performance benefits. Fully realizing these benefits requires the la…
Buddy Compression: Enabling Larger Memory for Deep Learning and HPC Workloads on GPUs
Esha Choukse, Michael Sullivan, Mike O'Connor +4
GPUs offer orders-of-magnitude higher memory bandwidth than traditional CPU-only systems. However, GPU device memory tends to be relatively small and the memory capacity can not be…