7 papers
Don't Overthink It: Inter-Rollout Action Agreement as a Free Adaptive-Compute Signal for LLM Agents
Khushal Sethi
Inference-time compute scaling has emerged as a powerful technique for improving the reliability of large language model (LLM) agents, but existing methods apply compute uniformly:…
Optimized Implementation of Neuromorphic HATS Algorithm on FPGA
Khushal Sethi, Manan Suri
In this paper, we present first-ever optimized hardware implementation of a state-of-the-art neuromorphic approach Histogram of Averaged Time Surfaces (HATS) algorithm to event-bas…
Low-Power Hardware-Based Deep-Learning Diagnostics Support Case Study
Khushal Sethi, Vivek Parmar, Manan Suri
Deep learning research has generated widespread interest leading to emergence of a large variety of technological innovations and applications. As significant proportion of deep le…
DRAGON (Differentiable Graph Execution) : A suite of Hardware Simulation and Optimization tools for Modern AI/Non-AI Workloads
Khushal Sethi
We introduce DRAGON, a fast and explainable hardware simulation and optimization toolchain that enables hardware architects to simulate hardware designs, and to optimize hardware d…
Efficient On-Chip Communication for Parallel Graph-Analytics on Spatial Architectures
Khushal Sethi
Large-scale graph processing has drawn great attention in recent years. Most of the modern-day datacenter workloads can be represented in the form of Graph Processing such as MapRe…
NV-Fogstore : Device-aware hybrid caching in fog computing environments
Khushal Sethi, Manan Suri
Edge caching via the placement of distributed storages throughout the network is a promising solution to reduce latency and network costs of content delivery. With the advent of th…
Design Space Exploration of Algorithmic Multi-Port Memories in High-Performance Application-Specific Accelerators
Khushal Sethi
Memory load/store instructions consume an important part in execution time and energy consumption in domain-specific accelerators. For designing highly parallel systems, available…