LIU Weichen

Appointment: Nanyang Assistant Professor

Research topics:
• Embedded and Real-Time Systems
• Many-Core Systems
• Electronic/Photonic Network-on-Chip
• Machine Learning Acceleration
• Computer Architecture

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831 to 840 of 1,021 Results

Related Data for: Efficient FPGA-based sparse matrix-vector multiplication with data reuse-aware compression Sep 20, 2023 - Li Shiqing Li, Shiqing; Liu, Di; Liu, Weichen, 2023, "Related Data for: Efficient FPGA-based sparse matrix-vector multiplication with data reuse-aware compression", https://doi.org/10.21979/N9/EXZ0Y3, DR-NTU (Data), V1 The code for the paper: Efficient FPGA-based sparse matrix-vector multiplication with data reuse-aware compression
Replication Data for: Crossbar-Aligned & Integer-Only Neural Network Compression for Efficient In-Memory Acceleration Mar 30, 2023 - Huai Shuo Huai, Shuo; Liu, Weichen, 2023, "Replication Data for: Crossbar-Aligned & Integer-Only Neural Network Compression for Efficient In-Memory Acceleration", https://doi.org/10.21979/N9/OVGZZ1, DR-NTU (Data), V1 Codes for "Crossbar-Aligned & Integer-Only Neural Network Compression for Efficient In-Memory Acceleration"
quantize.py Mar 30, 2023 - Replication Data for: Crossbar-Aligned & Integer-Only Neural Network Compression for Efficient In-Memory Acceleration Python Source Code - 71.6 KB - MD5: fb1def223697880e308ae2776ac0c452
resnet.py Mar 30, 2023 - Replication Data for: Crossbar-Aligned & Integer-Only Neural Network Compression for Efficient In-Memory Acceleration Python Source Code - 5.1 KB - MD5: 51fc7dd8ee30923e3896fa6030719a27
train_cifar.py Mar 30, 2023 - Replication Data for: Crossbar-Aligned & Integer-Only Neural Network Compression for Efficient In-Memory Acceleration Python Source Code - 18.0 KB - MD5: ed60c86e2d73e2290f6d1260da182a10
variation_calculation.py Mar 30, 2023 - Replication Data for: Crossbar-Aligned & Integer-Only Neural Network Compression for Efficient In-Memory Acceleration Python Source Code - 4.9 KB - MD5: fa30542bbd47bee9cefb75fd2cc47fb8
vgg.py Mar 30, 2023 - Replication Data for: Crossbar-Aligned & Integer-Only Neural Network Compression for Efficient In-Memory Acceleration Python Source Code - 1.9 KB - MD5: 298b5cf8fe2b33b52c03ec04bdaba946
Replication Data for: iMAD: An In-Memory Accelerator for AdderNet with Efficient 8-bit Addition and Subtraction Operations May 12, 2022 - Zhu Shien Zhu, Shien; Li, Shiqing; Liu, Weichen, 2022, "Replication Data for: iMAD: An In-Memory Accelerator for AdderNet with Efficient 8-bit Addition and Subtraction Operations", https://doi.org/10.21979/N9/JNFW9P, DR-NTU (Data), V2, UNF:6:L3+xW/BxBE6fYNWBm4ta6Q== [fileUNF] The simulation code, experiment results, and graphs used in the GLSVLSI 2022 paper: iMAD: An In-Memory Accelerator for AdderNet with Efficient 8-bit Addition and Subtraction Operations
CAPIM-00s11_voltage-08-10_SL-10-04_MUX8.png May 12, 2022 - Replication Data for: iMAD: An In-Memory Accelerator for AdderNet with Efficient 8-bit Addition and Subtraction Operations PNG Image - 588.6 KB - MD5: 5f86c21b93f8e286e9ca190f2e24cee2
CAPIM-11a00_voltage-08-10_SL-071-04_MUX8.png May 12, 2022 - Replication Data for: iMAD: An In-Memory Accelerator for AdderNet with Efficient 8-bit Addition and Subtraction Operations PNG Image - 553.3 KB - MD5: a769189212261a66de5745051fd1ff56

Related Data for: Efficient FPGA-based sparse matrix-vector multiplication with data reuse-aware compression

Sep 20, 2023 - Li Shiqing

Li, Shiqing; Liu, Di; Liu, Weichen, 2023, "Related Data for: Efficient FPGA-based sparse matrix-vector multiplication with data reuse-aware compression", https://doi.org/10.21979/N9/EXZ0Y3, DR-NTU (Data), V1

The code for the paper: Efficient FPGA-based sparse matrix-vector multiplication with data reuse-aware compression

Replication Data for: Crossbar-Aligned & Integer-Only Neural Network Compression for Efficient In-Memory Acceleration

Mar 30, 2023 - Huai Shuo

Huai, Shuo; Liu, Weichen, 2023, "Replication Data for: Crossbar-Aligned & Integer-Only Neural Network Compression for Efficient In-Memory Acceleration", https://doi.org/10.21979/N9/OVGZZ1, DR-NTU (Data), V1

Codes for "Crossbar-Aligned & Integer-Only Neural Network Compression for Efficient In-Memory Acceleration"

quantize.py

Mar 30, 2023 - Replication Data for: Crossbar-Aligned & Integer-Only Neural Network Compression for Efficient In-Memory Acceleration

Python Source Code - 71.6 KB -

resnet.py

Mar 30, 2023 - Replication Data for: Crossbar-Aligned & Integer-Only Neural Network Compression for Efficient In-Memory Acceleration

Python Source Code - 5.1 KB -

train_cifar.py

Mar 30, 2023 - Replication Data for: Crossbar-Aligned & Integer-Only Neural Network Compression for Efficient In-Memory Acceleration

Python Source Code - 18.0 KB -

variation_calculation.py

Mar 30, 2023 - Replication Data for: Crossbar-Aligned & Integer-Only Neural Network Compression for Efficient In-Memory Acceleration

Python Source Code - 4.9 KB -

vgg.py

Mar 30, 2023 - Replication Data for: Crossbar-Aligned & Integer-Only Neural Network Compression for Efficient In-Memory Acceleration

Python Source Code - 1.9 KB -

Replication Data for: iMAD: An In-Memory Accelerator for AdderNet with Efficient 8-bit Addition and Subtraction Operations

May 12, 2022 - Zhu Shien

Zhu, Shien; Li, Shiqing; Liu, Weichen, 2022, "Replication Data for: iMAD: An In-Memory Accelerator for AdderNet with Efficient 8-bit Addition and Subtraction Operations", https://doi.org/10.21979/N9/JNFW9P, DR-NTU (Data), V2, UNF:6:L3+xW/BxBE6fYNWBm4ta6Q== [fileUNF]

The simulation code, experiment results, and graphs used in the GLSVLSI 2022 paper: iMAD: An In-Memory Accelerator for AdderNet with Efficient 8-bit Addition and Subtraction Operations

CAPIM-00s11_voltage-08-10_SL-10-04_MUX8.png

May 12, 2022 - Replication Data for: iMAD: An In-Memory Accelerator for AdderNet with Efficient 8-bit Addition and Subtraction Operations

PNG Image - 588.6 KB -

CAPIM-11a00_voltage-08-10_SL-071-04_MUX8.png

May 12, 2022 - Replication Data for: iMAD: An In-Memory Accelerator for AdderNet with Efficient 8-bit Addition and Subtraction Operations

PNG Image - 553.3 KB -

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