2 citations · 10 across the 21 of their papers we have counts for
5 papers · 1 filter
DX100: A Programmable Data Access Accelerator for Indirection
Alireza Khadem, Kamalavasan Kamalakkannan, Zhenyan Zhu +8
Indirect memory accesses frequently appear in applications where memory bandwidth is a critical bottleneck. Prior indirect memory access proposals, such as indirect prefetchers, ru…
NMP-PaK: Near-Memory Processing Acceleration of Scalable De Novo Genome Assembly
Heewoo Kim, Sanjay Sri Vallabh Singapuram, Haojie Ye +4
De novo assembly enables investigations of unknown genomes, paving the way for personalized medicine and disease management. However, it faces immense computational challenges aris…
Multi-Dimensional Vector ISA Extension for Mobile In-Cache Computing
Alireza Khadem, Daichi Fujiki, Hilbert Chen +4
In-cache computing technology transforms existing caches into long-vector compute units and offers low-cost alternatives to building expensive vector engines for mobile CPUs. Unfor…
Vector-Processing for Mobile Devices: Benchmark and Analysis
Alireza Khadem, Daichi Fujiki, Nishil Talati +2
Vector processing has become commonplace in today's CPU microarchitectures. Vector instructions improve performance and energy which is crucial for resource-constraint mobile devic…
Accelerating Graph Analytics on a Reconfigurable Architecture with a Data-Indirect Prefetcher
Yichen Yang, Jingtao Li, Nishil Talati +5
The irregular nature of memory accesses of graph workloads makes their performance poor on modern computing platforms. On manycore reconfigurable architectures (MRAs), in particula…