3 papers
cs.AR2026
DTX: A Throughput-First Training Accelerator for Diffusion and Transformer Models
Shashank
DTX is a throughput-first training accelerator for diffusion and transformer models. Any summation serialized through a single FP32 adder is a loop-carried dependence that pins a m…
cs.AR2026
Transformer Accelerator (TFA): A Macro-Op INT8 Hardware Chip for Transformer Inference and Machine Translation
Shashank
We present the Transformer Accelerator (TFA), a synthesizable, parameterizable INT8 memory-to-memory engine for transformer inference. One time-multiplexed datapath handles prompt…
cs.LG2026
Attractor Patch Networks: Reducing Catastrophic Forgetting with Routed Low-Rank Patch Experts
Shashank
Transformers achieve strong language modeling accuracy, yet their position-wise feed-forward networks (FFNs) are dense, globally shared, and typically updated end to end. These pro…