Toward Standardized Near-Data Processing with
Unrestricted Data Placement for GPUs
SessionGPUs and Communication
Event Type
Paper
TimeWednesday, November 15th11:30am -
12pm
Location402-403-404
Description3D-stacked memory devices with processing logic can
help alleviate the memory bandwidth bottleneck in GPUs.
However, in order for such Near-Data Processing (NDP)
memory stacks to be used for different GPU
architectures, it is desirable to standardize the NDP
architecture. Our proposal enables this standardization
by allowing data to be spread across multiple memory
stacks as is the norm in high-performance systems
without an MMU on the NDP stack. The keys to this
architecture are the ability to move data between memory
stacks as required for computation, and a partitioned
execution mechanism that offloads memory-intensive
application segments onto the NDP stack and decouples
address translation from DRAM accesses. By enhancing
this system with a smart offload selection mechanism
that is cognizant of the compute capability of the NDP
and cache locality on the host processor, system
performance and energy are improved by up to 66.8% and
37.6%, respectively.
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