1 citations · 1 across the 10 of their papers we have counts for
12 papers
BOOST: Concurrent Access to Host Memory and HBM to Accelerate LLM Inference
Anish Saxena, Jae Hyung Ju, Hritvik Taneja +4
GPU memory bandwidth and capacity limit throughput in large language model (LLM) inference. The GPU memory system consists of a primary tier of high-bandwidth memory (HBM) and a se…
From Fleet to Lab: Revisiting the Security and Complexity of Industrial Rowhammer Mitigation
Hritvik Taneja, Moinuddin Qureshi
This paper studies efficient and secure Rowhammer mitigation at the Memory-Controller (MC). Rowhammer mitigation faces a fundamental tradeoff between tracking storage and mitigatio…
CODA: How to Mitigate ColumnDisturb for (Almost) Free?
Moinuddin Qureshi
ColumnDisturb is a new data-disturbance error in which activations to an aggressor row cause bitflips in a victim row located hundreds of rows away (intra-subarray bitflips) and in…
SiFAR: Synchronization-Free All-Reduce for Low-Latency LLM Inference
Hritvik Taneja, Anish Saxena, Abhishek Revinipati +3
The rise of reasoning models and agentic systems has made LLM token-generation latency a key bottleneck. Unlike chatbots, whose latency gains saturate at human reading speed, these…
TileLens: Efficiently Using Large-Granularity Memory Systems with Transparent Two-Dimensional Memory Layout
Jae Hyung Ju, Euijun Chung, Hritvik Taneja +4
Large Language Model (LLM) inference is bottlenecked by the capacity and bandwidth of GPU High-Bandwidth Memory (HBM). Recent proposals, such as High-Bandwidth Flash (HBF) and RoMe…
The Avatar Cache: Enabling On-Demand Security with Morphable Cache Architecture
Anubhav Bhatla, Navneet Navneet, Moinuddin Qureshi +1
The sharing of the last-level cache (LLC) among multiple cores makes it vulnerable to cross-core conflict- and occupancy-based attacks. Despite extensive prior work, modern process…
Computer Science Challenges in Quantum Computing: Early Fault-Tolerance and Beyond
Jens Palsberg, Jason Cong, Yufei Ding +7
Quantum computing is entering a period in which progress will be shaped as much by advances in computer science as by improvements in hardware. The central thesis of this report is…
Utility-Driven Speculative Decoding for Mixture-of-Experts
Anish Saxena, Po-An Tsai, Hritvik Taneja +2
GPU memory bandwidth is the main bottleneck for low-latency Large Language Model (LLM) inference. Speculative decoding leverages idle GPU compute by using a lightweight drafter to…
RogueRFM: Attacking Refresh Management for Covert-Channel and Denial-of-Service
Hritvik Taneja, Moinuddin Qureshi
With lowering thresholds, transparently defending against Rowhammer within DRAM is challenging due to the lack of time to perform mitigation. Commercially deployed in-DRAM defenses…
MINT: Securely Mitigating Rowhammer with a Minimalist In-DRAM Tracker
Moinuddin Qureshi, Salman Qazi, Aamer Jaleel
This paper investigates secure low-cost in-DRAM trackers for mitigating Rowhammer (RH). In-DRAM solutions have the advantage that they can solve the RH problem within the DRAM chip…
ImPress: Securing DRAM Against Data-Disturbance Errors via Implicit Row-Press Mitigation
Moinuddin Qureshi, Anish Saxena, Aamer Jaleel
DRAM cells are susceptible to Data-Disturbance Errors (DDE), which can be exploited by an attacker to compromise system security. Rowhammer is a well-known DDE vulnerability that o…
MOAT: Securely Mitigating Rowhammer with Per-Row Activation Counters
Moinuddin Qureshi, Salman Qazi
The security vulnerabilities due to Rowhammer have worsened over the last decade, with existing in-DRAM solutions, such as TRR, getting broken with simple patterns. In response, th…