Pinned Repositories
lisa
A portable framework to map DFG (dataflow graph, representing an application) on spatial accelerators.
morpher
An Open-Source Tool for CGRA Accelerators
ALADDIN
A pre-RTL, power-performance model for fixed-function accelerators
Compiler-benchmark-suites
A list of benchmark suites used in the research related to compilers, program performance, scientific computations etc.
dMazeRunner
dMazeRunner: Dataflow acceleration optimization infrastructure for coarse-grained programmable accelerators
dsa-framework
Release of stream-specialization software/hardware stack.
enable_arm_pmu
Enable user-mode access to ARMv7/Linux performance counters
Graphs
Graphs, BFS, DFS, connected components
greenpepper
MachSuite
Benchmarks for Accelerator Design and Customized Architectures
zhaoying-LI's Repositories
zhaoying-LI/ALADDIN
A pre-RTL, power-performance model for fixed-function accelerators
zhaoying-LI/Compiler-benchmark-suites
A list of benchmark suites used in the research related to compilers, program performance, scientific computations etc.
zhaoying-LI/dMazeRunner
dMazeRunner: Dataflow acceleration optimization infrastructure for coarse-grained programmable accelerators
zhaoying-LI/dsa-framework
Release of stream-specialization software/hardware stack.
zhaoying-LI/enable_arm_pmu
Enable user-mode access to ARMv7/Linux performance counters
zhaoying-LI/Graphs
Graphs, BFS, DFS, connected components
zhaoying-LI/greenpepper
zhaoying-LI/MachSuite
Benchmarks for Accelerator Design and Customized Architectures
zhaoying-LI/mm-cot
Official implementation for "Multimodal Chain-of-Thought Reasoning in Language Models" (stay tuned and more will be updated)
zhaoying-LI/nvdla_note
zhaoying-LI/obj_fps
zhaoying-LI/odla_data
zhaoying-LI/PolyBenchC-4.2.1
PolyBench/C benchmark suite (version 4.2.1 beta) from http://web.cse.ohio-state.edu/~pouchet/software/polybench/
zhaoying-LI/stack-manuca-os
zhaoying-LI/wifi_drive
zhaoying-LI/zhaoying-LI.github.io
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes