Search Results - "Parallel Programming Languages"

Special issue on advances in techniques for assessment performance portability of HPC applications by Marowka, Ami, Stpiczyński, Przemysław, Wyrzykowski, Roman

“…This special issue aims to present new developments and advances in techniques for assessment performance portability of high performance computing…”
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Splitwise: Efficient Generative LLM Inference Using Phase Splitting by Patel, Pratyush, Choukse, Esha, Zhang, Chaojie, Shah, Aashaka, Goiri, Inigo, Maleki, Saeed, Bianchini, Ricardo

“…Generative large language model (LLM) applications are growing rapidly, leading to large-scale deployments of expensive and power-hungry GPUs. Our…”
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Polygeist: Raising C to Polyhedral MLIR by Moses, William S., Chelini, Lorenzo, Zhao, Ruizhe, Zinenko, Oleksandr

“…We present Polygeist, a new compilation flow that connects the MLIR compiler infrastructure to cutting edge polyhedral optimization tools. It consists of a C…”
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Qilin: exploiting parallelism on heterogeneous multiprocessors with adaptive mapping by Luk, Chi-Keung, Hong, Sunpyo, Kim, Hyesoon

“…Heterogeneous multiprocessors are increasingly important in the multi-core era due to their potential for high performance and energy efficiency. In order for…”
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SimplePIM: A Software Framework for Productive and Efficient Processing-in-Memory by Chen, Jinfan, Gomez-Luna, Juan, El Hajj, Izzat, Guo, Yuxin, Mutlu, Onur

“…Data movement between memory and processors is a major bottleneck in modern computing systems. The processing-in-memory (PIM) paradigm aims to alleviate this…”
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Opportunistically Parallel Lambda Calculus by Mell, Stephen, Kallas, Konstantinos, Zdancewic, Steve, Bastani, Osbert

“…Scripting languages are widely used to compose external calls such as native libraries and network services. In such scripts, execution time is often dominated…”
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Dynamically Fusing Python HPC Kernels by Al Awar, Nader, Naeem, Muhammad Hannan, Almgren-Bell, James, Biros, George, Gligoric, Milos

“…Recent trends in high-performance computing show an increase in the adoption of performance portable frameworks such as Kokkos and interpreted languages such…”
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Mars: A MapReduce Framework on graphics processors by He, Bingsheng, Fang, Wenbin, Luo, Qiong, Govindaraju, Naga K., Wang, Tuyong

“…We design and implement Mars, a MapReduce framework, on graphics processors (GPUs). MapReduce is a distributed programming framework originally proposed by…”
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Efficient Execution of OpenMP on GPUs by Huber, Joseph, Cornelius, Melanie, Georgakoudis, Giorgis, Tian, Shilei, Diaz, Jose M Monsalve, Dinel, Kuter, Chapman, Barbara, Doerfert, Johannes

“…OpenMP is the preferred choice for CPU parallelism in High-Performance-Computing (HPC) applications written in C, C++, or Fortran. As HPC systems became…”
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Python shared atomic data types by Ren, Xiquan

“…Although atomicity plays a key role in data operations of shared variables in parallel computation, researchers haven't treated atomicity in Python in much…”
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PID-Comm: A Fast and Flexible Collective Communication Framework for Commodity Processing-in-DIMM Devices by Noh, Si Ung, Hong, Junguk, Lim, Chaemin, Park, Seongyeon, Kim, Jeehyun, Kim, Hanjun, Kim, Youngsok, Lee, Jinho

“…Recent dual in-line memory modules (DIMMs) are starting to support processing-in-memory (PIM) by associating their memory banks with processing elements (PEs),…”
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Cognitive Correlative Encoding for Genome Sequence Matching in Hyperdimensional System by Poduval, Prathyush, Zou, Zhuowen, Yin, Xunzhao, Sadredini, Elaheh, Imani, Mohsen

“…Pattern matching is one of the key algorithms in identifying and analyzing genomic data. In this paper, we propose HYPERS, a novel framework supporting highly…”
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HiSpTRSV: Exploring Tile-Level Parallelism for SpTRSV Acceleration on FPGAs by Sun, Fan, Dong, Fang, Shen, Dian

“…Sparse Triangular Solve (SpTRSV) is a critical level2 kernel in sparse Basic Linear Algebra Subprograms (BLAS). While Field-Programmable Gate Array (FPGA)…”
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Adaptive heterogeneous scheduling for integrated GPUs by Kaleem, Rashid, Barik, Rajkishore, Shpeisman, Tatiana, Lewis, Brian T., Chunling Hu, Pingali, Keshav

“…Many processors today integrate a CPU and GPU on the same die, which allows them to share resources like physical memory and lowers the cost of CPU-GPU…”
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An effective GPU implementation of breadth-first search by Lijuan Luo, Wong, Martin, Wen-mei Hwu

“…Breadth-first search (BFS) has wide applications in electronic design automation (EDA) as well as in other fields. Researchers have tried to accelerate BFS on…”
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Scalable, Programmable and Dense: The HammerBlade Open-Source RISC-V Manycore by Jung, Dai Cheol, Ruttenberg, Max, Gao, Paul, Davidson, Scott, Petrisko, Daniel, Li, Kangli, Kamath, Aditya K, Cheng, Lin, Xie, Shaolin, Pan, Peitian, Zhao, Zhongyuan, Yue, Zichao, Veluri, Bandhav, Muralitharan, Sripathi, Sampson, Adrian, Lumsdaine, Andrew, Zhang, Zhiru, Batten, Christopher, Oskin, Mark, Richmond, Dustin, Taylor, Michael Bedford

“…Existing tiled manycore architectures propose to convert abundant silicon resources into general-purpose parallel processors with unmatched computational…”
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SafeRace: Assessing and Addressing WebGPU Memory Safety in the Presence of Data Races by Levine, Reese, Lee, Ashley, Abbas, Neha, Little, Kyle, Sorensen, Tyler

“…In untrusted execution environments such as web browsers, code from remote sources is regularly executed. To harden these environments against attacks,…”
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PairGraph: An Efficient Search-space-aware Accelerator for High-performance Concurrent Pairwise Queries by Fu, Yutao, Long, Zhongtian, Zhang, Yu, He, Zirui, Zhao, Jin, Niu, Qiyuan, Wang, Zixiao, Jin, Hai

“…Pairwise queries have been widely used in many applications. Although several approaches have been recently proposed to accelerate a single query, they still…”
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Automatic Parallelism Management by Westrick, Sam, Fluet, Matthew, Rainey, Mike, Acar, Umut A.

“…On any modern computer architecture today, parallelism comes with a modest cost, born from the creation and management of threads or tasks. Today, programmers…”
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Evaluation of Blue Gene/Q hardware support for transactional memories by Amy Wang, Gaudet, Matthew, Wu, Peng, Amaral, Jose Nelson, Ohmacht, Martin, Barton, Christopher, Silvera, Raul, Michael, Maged

“…This paper describes an end-to-end system implementation of the transactional memory (TM) programming model on top of the hardware transactional memory (HTM)…”
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