搜尋

會員登入

搜尋

導覽

會員
廣告
廣告

NEUCHIPS Delivers Industry Leading Results for MLPerf v3.0 DLRM Inference Benchmarking

瀏覽次數:6466

TAIPEI, Taiwan - NEUCHIPS, the leader in AI ASIC platforms for deep learning recommendation, participated in MLPerf(TM) v3.0 with their RecAccel(TM) N3000 and demonstrated industry-leading performance and power efficiency. The RecAccel(TM) N3000 system delivered 1.7x better perf-per-watt for inference DLRM while maintaining 99.9% accuracy leveraging its INT8 calibrator.

The RecAccel(TM) Quad-N3000 PCIe card is expected to increase perf-per-watt 2.2x while also delivering the lowest total cost of ownership (TCO). These results give cloud service providers confidence to choose a new solution on existing and future data center platforms.

MLPerf(TM) v3.0 testing was performed on a GIGABYTE G482-Z54 server with AMD EPYC(TM) 7452 32-core CPU and contained eight RecAccel(TM)-N3000-32G-PCIe cards. During the system testing, the RecAccel(TM) N3000 performance resulted in nearly 100% scaling across each card.

"We deliver high-performance computing products that help intelligent systems effectively manage complex data sets," said Kumaran Siva, corporate vice president, Strategic Business Development, AMD. "We are extremely proud of the joint work we have done with NEUCHIPS to achieve leadership performance and power efficiency for DLRM inference in MLPerf(TM) v3.0 using AMD EPYC processors. We look forward to continue working with NEUCHIPS to deliver industry-leading AI solutions."

"We were thrilled to participate in MLPerf(TM) v3.0 and achieve our goal to deliver the world's most energy-efficient DLRM inference platform with the first domain specific architecture," said Youn-Long Lin, the CEO and Chairman of NEUCHIPS. "We look forward to working with the cloud ecosystem to support industry sustainability initiatives."

稀土棋局下的台灣解方:從供應鏈韌性看關鍵礦物合作新契機
特別企劃半導體

稀土棋局下的台灣解方:從供應鏈韌性看關鍵礦物合作新契機

稀土與關鍵礦物已成全球科技競爭與經濟安全的重要戰略資源。面對供應鏈高度集中與地緣風險升高,台灣如何透過國際合作、技術替代、戰略儲備與城市採礦,建立自主且具韌性的關鍵礦物供應體系?

稀土與關鍵礦物已成全球科技競爭與經濟安全的重要戰略資源。面對供應鏈高度集中與地緣風險升高,台灣如何透過國際合作、技術替代、戰略儲備與城市採礦,建立自主且具韌性的關鍵礦物供應體系?

關鍵字:deep learning