5 citations · 7 across the 4 of their papers we have counts for
3 papers · 1 filter
SCALE-Sim EVA: Design Principles for an Extensible, Visualizable, and Adaptable Accelerator Simulation Framework
Jingtian Dang, Ritik Raj, Tushar Krishna
Modern AI accelerators increasingly combine heterogeneous compute units, hierarchical memories, local buffers, and specialized data movement paths. This diversity makes fixed accel…
Enabling AI ASICs for Zero Knowledge Proof
Jianming Tong, Jingtian Dang, Simon Langowski +6
Zero-knowledge proof (ZKP) provers remain costly because multi-scalar multiplication (MSM) and number-theoretic transforms (NTTs) dominate runtime as they need significant computat…
SCALE-Sim TPU: Validating and Extending SCALE-Sim for TPUs
Jingtian Dang, Ritik Raj, Changhai Man +2
Cycle-accurate simulators are widely used to study systolic accelerators, yet their accuracy and usability are often limited by weak validation against real hardware and poor integ…