VeriSilicon’s Scalable High-Performance GPGPU-AI Computing IPs Empower Automotive and Edge Server AI Solutions>

(BUSINESS WIRE)--VeriSilicon (688521.SH) today announced the latest advancements in its high-performance and scalable GPGPU-AI computing IPs, which are now empowering next-generation automotive electronics and edge server applications. Combining programmable parallel computing with a dedicated Artificial Intelligence (AI) accelerator, these IPs offer exceptional computing density for demanding AI workloads such as Large Language Model (LLM) inference, multimodal perception, and real-time decision-making in thermally and power-constrained environments. VeriSilicon’s GPGPU-AI computing IPs are based on a high-performance General Purpose Graphics Processing Unit (GPGPU) architecture with an integrated dedicated AI accelerator, delivering outstanding computing capabilities to AI applications. The programmable AI accelerator and sparsity-aware computing engine accelerate transformer-based and matrix-intensive models through advanced scheduling techniques. These IPs also support a broad range of data formats for mixed-precision computing, including INT4/8, FP4/8, BF16, FP16/32/64, and TF32, and are designed with high-bandwidth interfaces of 3D-stacked memory, LPDDR5X, ...(BUSINESS WIRE)--VeriSilicon (688521.SH) today announced the latest advancements in its high-performance and scalable GPGPU-AI computing IPs, which are now empowering next-generation automotive electronics and edge server applications. Combining programmable parallel computing with a dedicated Artificial Intelligence (AI) accelerator, these IPs offer exceptional computing density for demanding AI workloads such as Large Language Model (LLM) inference, multimodal perception, and real-time decision-making in thermally and power-constrained environments. VeriSilicon’s GPGPU-AI computing IPs are based on a high-performance General Purpose Graphics Processing Unit (GPGPU) architecture with an integrated dedicated AI accelerator, delivering outstanding computing capabilities to AI applications. The programmable AI accelerator and sparsity-aware computing engine accelerate transformer-based and matrix-intensive models through advanced scheduling techniques. These IPs also support a broad range of data formats for mixed-precision computing, including INT4/8, FP4/8, BF16, FP16/32/64, and TF32, and are designed with high-bandwidth interfaces of 3D-stacked memory, LPDDR5X, ...{}