煤渣
发表于 2025-3-26 23:13:24
TopKmer: Parallel High Frequency K-mer Counting on Distributed Memoryastq files and complete queries in 1 s for 1 billion k-mers, with a scaling efficiency of 95%. Compared with the state of the art, the counting table’s memory usage is reduced by 50% with no performance degradation.
说笑
发表于 2025-3-27 02:12:42
Adjust: An Online Resource Adjustment Framework for Microservice Programs Adjust identifies the causes of the abnormality of microservice programs, and determines performance assurance strategies on both system and microservice levels. By dynamically adjusting the resource allocation, Adjust can effectively guarantee the performance of microservice programs and improves system resource utilization at the same time.
纵火
发表于 2025-3-27 07:57:02
Conference proceedings 2022n Jinan, China, during September 24-25, 2022...The 23 full papers and 8 short papers presented in this volume were carefully reviewed and selected from 89 submissions. They were organized in topical sections as follows: computer architecture; cloud computing; deep learning; emerging applications; an
MOTTO
发表于 2025-3-27 10:54:59
Cloud-Native Server Consolidation for Energy-Efficient FaaS Deploymenty, we propose ., a software-hardware co-design solution to offer differentiated cloud-native server consolidation. We build a proof-of-concept framework and show that . can improve the energy efficiency of tail function deployment by up to 23%.
genuine
发表于 2025-3-27 15:48:50
http://reply.papertrans.cn/67/6629/662882/662882_35.png
Concomitant
发表于 2025-3-27 20:07:09
http://reply.papertrans.cn/67/6629/662882/662882_36.png
Morbid
发表于 2025-3-28 01:12:47
SADD: A Novel Systolic Array Accelerator with Dynamic Dataflow for Sparse GEMM in Deep Learningo the computing environment. The experimental results show that the SDD in the SADD perform efficiently in any computing environment. When running the AlexNet, the performance of the SADD is . better than the TPU. In addition, the SADD brings only a small additional hardware overhead.
使纠缠
发表于 2025-3-28 05:02:36
CSR&RV: An Efficient Value Compression Format for Sparse Matrix-Vector Multiplication real-world matrices. Experimental results show that CSR &RV can achieve a speedup up to 3.86. (1.66. on average) and a speedup up to 12.42. (3.12. on average) for single-core and multi-core throughput, respectively. Meanwhile, our format can reduce the memory space by 48.57% on average.
神经
发表于 2025-3-28 06:20:12
0302-9743 was held in Jinan, China, during September 24-25, 2022...The 23 full papers and 8 short papers presented in this volume were carefully reviewed and selected from 89 submissions. They were organized in topical sections as follows: computer architecture; cloud computing; deep learning; emerging applic
innate
发表于 2025-3-28 14:05:58
http://reply.papertrans.cn/67/6629/662882/662882_40.png