We are proud to announce that the @EPSRC@spatialmlnet project has completed. This feed may not be maintained in the future. Thank you to all who contributed to the successes documented in the history of this feed. We have built a self-sustaining community to be proud of.
"Beyond Network Switching: FPGA-based Switch Architecture for Fast and Accurate Ensemble Learning" by @spatialmlnet member Luk and coauthors, now at https://t.co/uD5LjW27qi
"Learning to Compare Hardware Designs for High-Level Synthesis" by @spatialmlnet members Sohrabizadeh and Cong and their coauthors, now at https://t.co/AeiYSc6Y8r
"H2PIPE: High throughput CNN Inference on FPGAs with High-Bandwidth Memory" by @spatialmlnet affiliate Betz and coauthors. Now at: https://t.co/AtwD4FFWLE
"Highly-Parallel CNN Accelerator for RepVGG-like Network Training on FPGAs" by @spatialmlnet affiliates Boland and Leong and coauthors, now at https://t.co/gt6RYGbTyp
"FPGA Acceleration of Dynamic Neural Networks: Challenges and Advancements" by @spatialmlnet students Dimitriou and Bings and investigators @jon_hare and @g_merrett now at https://t.co/QPDMQQaxbu
"Multi-Token Joint Speculative Decoding for Accelerating Large Language Model Inference" by @spatialmlnet affiliate Cong and coauthors, now at https://t.co/3HfGyjDSEt
"Accelerating MRI Uncertainty Estimation with Mask-based Bayesian Neural Network" by @spatialmlnet affiliate Luk and coauthors. Now at https://t.co/DmiPsGxxlR
Kratos: An FPGA Benchmark for Unrolled DNNs with Fine-Grained Sparsity and Mixed Precision by @spatialmlnet affiliates Chen and @mohsaied and coauthor. Now at https://t.co/5VVbhrg02f
"ShadowLLM: Predictor-based Contextual Sparsity for Large Language Models" by @spatialmlnet affiliates @AmishAcorns, Zhang, @mohsaied and coauthors. Now at https://t.co/aSXmdcMsYo
"ShadowLLM: Predictor-based Contextual Sparsity for Large Language Models" by @spatialmlnet affiliates @AmishAcorns, Zhang, @mohsaied and coauthors. Now at https://t.co/aSXmdcMsYo
"Towards Open Respiratory Acoustic Foundation Models: Pretraining and Benchmarking" by @spatialmlnet affiliate @jag_jagmohan and coauthors. Now at https://t.co/TgHjH7S2Vt
"Optimised Grouped-Query Attention Mechanism for Transformers" by @spatialmlnet affiliates Zhang, @gconstantinides, @aaronzhao123 and coauthors. Now at https://t.co/pqWdH6jvRp