Accelerator level parallelismSchedulingCo-executionIn the era of heterogeneous computing, a new paradigm called accelerator level parallelism (ALP) has emerged. In ALP, accelerators are used concurrently to provide unprecedented levels of performance and energy efficiency. To reach that there are many ...
According to an example, an indexing accelerator with memory-level parallelism (MLP) support may include a request decoder to receive indexing requests. The request decoder may incl
According to an example, an indexing accelerator with memory-level parallelism (MLP) support may include a request decoder to receive indexing requests. The request decoder may include a plurality of configuration registers. A controller may be communicatively coupled to the request decoder to support...
One such simulation, RSim, was previously performed on single workstations, however, the increase in detail required for newer ToF hardware necessitates cluster-level parallelism in order to maintain an experiment latency which enables productive design work. Celerity is a high-level parallel API ...
Most frequently, an FPGA is used as an implementation platform in applications of graphics processing, as its structure can effectively exploit both spatial and temporal parallelism. Such parallelization techniques involve fundamental restrictions, namely being their dependence on both the processing model ...
Specialized accelerators can exploit spatial parallelism on both operations and data thanks to a dedicated microarchitecture with a better use of the hardware resources. Designers need to describe such components (including the resources, their interconnections, and the control logic) in proper hardware ...
Providing convenient APIs and notations for data parallelism which remain accessible for programmers while still providing good performance has been a long-term goal of researchers as well as language and library designers. C++20 introduces ranges and views, as well as the composition of operations ...
Providing convenient APIs and notations for data parallelism which remain accessible for programmers while still providing good performance has been a long
acceleratorFPGApythonHDLMost frequently, an FPGA is used as an implementation platform in applications of graphics processing, as its structure can effectively exploit both spatial and temporal parallelism. Such parallelization techniques involve fundamental restrictions, namely being their dependence on both ...
Most frequently, an FPGA is used as an implementation platform in applications of graphics processing, as its structure can effectively exploit both spatial and temporal parallelism. Such parallelization techniques involve fundamental restrictions, namely being their dependence on both the processing model ...