  Applications with irregular data structures, data-dependent control flows and
fine-grained data transfers (e.g., real-world graph computations) perform
poorly on cache-based systems. We propose the UpDown accelerator that supports
fine-grained execution with novel architecture mechanisms - lightweight
threading, event-driven scheduling, efficient ultra-short threads, and
split-transaction DRAM access with software-controlled synchronization. These
hardware primitives support software programmable events, enabling high
performance on diverse data structures and algorithms. UpDown also supports
scalable performance; hardware replication enables programs to scale up
performance. Evaluation results show UpDown's flexibility and scalability
enable it to outperform CPUs on graph mining and analytics computations by up
to 116-195x geomean speedup and more than 4x speedup over prior accelerators.
We show that UpDown generates high memory parallelism (~4.6x over CPU) required
for memory intensive graph computations. We present measurements that attribute
the performance of UpDown (23x architectural advantage) to its individual
architectural mechanisms. Finally, we also analyze the area and power cost of
UpDown's mechanisms for software programmability.
