Defines: Enabling fast exploration of the depth-first scheduling space for dnn accelerators through analytical modeling
DNN workloads can be scheduled onto DNN accelerators in many different ways: from layer-
by-layer scheduling to cross-layer depth-first scheduling (aka layer fusion, or cascaded …
by-layer scheduling to cross-layer depth-first scheduling (aka layer fusion, or cascaded …
Tinyvers: A tiny versatile system-on-chip with state-retentive eMRAM for ML inference at the extreme edge
Extreme edge devices or Internet-of-Things (IoT) nodes require both ultra-low power (ULP)
always-on (AON) processing as well as the ability to do on-demand sampling and …
always-on (AON) processing as well as the ability to do on-demand sampling and …
Teaal: A declarative framework for modeling sparse tensor accelerators
Over the past few years, the explosion in sparse tensor algebra workloads has led to a
corresponding rise in domain-specific accelerators to service them. Due to the irregularity …
corresponding rise in domain-specific accelerators to service them. Due to the irregularity …