1 citations · 1 across the 5 of their papers we have counts for
9 papers
Understanding the Power Consumption of Modern High Bandwidth Memory: Experimental Analysis and Modeling Using Real HBM2 DRAM Chips
Ataberk Olgun, Spiros Galanopoulos, Andreas Kosmas Kakolyris +4
We perform the first comprehensive experimental characterization of power consumed by real HBM2 DRAM chips. Our extensive characterization yields 1) the empirical basis for develop…
Terracotta: Enabling the Adoption of New DRAM Techniques via a Flexible DRAM Interface and Memory Controller
Harsh Songara, Konstantinos Kanellopoulos, F. Nisa Bostancı +6
DRAM continues to limit the performance, energy efficiency, and robustness of modern systems. Many prior works propose DRAM techniques that support in-DRAM computation, improve mem…
Valinor: Architectural Support for Fast, Energy-Efficient and Programmable Physical Memory Allocation
Konstantinos Kanellopoulos, Spiros Galanopoulos, Konstantinos Sgouras +7
Physical memory allocation establishes virtual-to-physical mappings on demand. In current systems, each minor page fault traps into the kernel and triggers pipeline flushes, stalls…
ColumnKeeper: Efficient Solutions to the ColumnDisturb Vulnerability in DRAM-based Systems
Andreas Kosmas Kakolyris, F. Nisa Bostanci, Ataberk Olgun +7
Modern DRAM chips are vulnerable to read disturbance phenomena such as RowHammer and RowPress, which induce bitflips after accessing nearby rows a certain number of times (the read…
Conduit: Programmer-Transparent Near-Data Processing Using Multiple Compute-Capable Resources in Solid State Drives
Rakesh Nadig, Vamanan Arulchelvan, Mayank Kabra +9
Solid-state drives (SSDs) are well suited for near-data processing (NDP) because they: (1) store large application datasets, and (2) support three NDP paradigms: in-storage process…
Revelator: Rapid Data Fetching via System-Software-Guided Hash-based Speculative Address Translation
Konstantinos Kanellopoulos, Konstantinos Sgouras, Harsh Songara +7
Address translation is a major performance bottleneck in modern computing systems. Predicting the physical address (PA) of requested data before address translation completes can h…
Harmonia: Enhancing Data Placement and Migration in Hybrid Storage Systems via Multi-Agent Reinforcement Learning
Rakesh Nadig, Vamanan Arulchelvan, Rahul Bera +7
Modern high-performance computing (HPC) environments rely on hybrid storage systems (HSS) that combine multiple storage devices with diverse latency, bandwidth, endurance, and capa…
SLO-aware GPU Frequency Scaling for Energy Efficient LLM Inference Serving
Andreas Kosmas Kakolyris, Dimosthenis Masouros, Petros Vavaroutsos +2
As Large Language Models (LLMs) gain traction, their reliance on power-hungry GPUs places ever-increasing energy demands, raising environmental and monetary concerns. Inference dom…
Virtuoso: Enabling Fast and Accurate Virtual Memory Research via an Imitation-based Operating System Simulation Methodology
Konstantinos Kanellopoulos, Konstantinos Sgouras, F. Nisa Bostanci +7
The unprecedented growth in data demand from emerging applications has turned virtual memory (VM) into a major performance bottleneck. Researchers explore new hardware/OS co-design…