Access more resources about UPMEM
We have gathered a selection of past and on-going works related to UPMEM’s technology, often involving renowned Universities with links to access to papers, videos and open source code when available. For clarity purposes sections are sorted by fields of interest:
- General overview and architecture
- General performances and micro-benchmarks
- Compiler / programming model
- Libraries
- Genomics & Bioinformatics
- Search
- Analytics & Database
- Machine Learning / Deep Learning
Last updated on May 2023
General overview and architecture
Title | Status | Authors | Paper/resource | Code |
---|---|---|---|---|
A survey on hardware accelerators: Taxonomy, trends, challenges, and perspectives | Published (JSA 2022) | University of Sienna / Huawei | Paper | N/A |
Architecture programming tools overview, showcasing genomics/analytics applications using UPMEM Processing In Memory | Published (HIPEAC 2021) | UPMEM | Video SDK Documentation | GitHub |
General performances and micro-benchmarks
Title | Status | Authors | Paper/resource | Code |
---|---|---|---|---|
Benchmarking a New Paradigm: An Experimental Analysis of a Real Processing-in-Memory Architecture | Published (2021) | ETH Zurich | Full paper Video | GitHub |
Benchmarking Memory-Centric Computing Systems: Analysis of Real Processing-In-Memory Hardware | Published (CUT 2021) | ETH Zurich | Paper Video | GitHub |
A Case Study of Processing-in-Memory in off-the-Shelf Systems | Published (USENIX 2021) | University of British Columbia | Paper Video | GitHub |
Compiler / programming model
Title | Status | Authors | Paper/resource | Code |
---|---|---|---|---|
CINM (Cinnamon): A Compilation Infrastructure for Heterogeneous Compute In-Memory and Compute Near-Memory Paradigms | Published (2023) | TU Dresden / Intel | Paper | Available soon |
Libraries
TITLE | STATUS | AUTHORS | PAPER/RESOURCE | CODE |
---|---|---|---|---|
TransPimLib: A Library for Efficient Transcendental Functions on Processing-in-Memory Systems | Published (ISPASS 2023) | ETH Zurich | Paper | GitHub |
SparseP: Towards Efficient Sparse Matrix Vector Multiplication on Real Processing-In-Memory Systems | Published (POMACS 2022) | ETH Zurich | Paper | GitHub |
Genomics & Bioinformatics
Title | Status | Authors | Paper/resource | Code |
---|---|---|---|---|
UpPipe: A Novel Pipeline Management on In-Memory Processors for RNA-seq Quantification | Paper accepted (DAC 2023) | National Cheng Kung University | Coming soon | Coming soon |
A Framework for High-throughput Sequence Alignment using Real Processing-in-Memory Systems | Published (Hi Comb 2022) | ETH Zurich | Paper | GitHub |
Variant Calling Parallelization on Processor-in-Memory Architecture | Published (BIBM 2021) | IRISA / CNRS / INRIA | Paper | GitHub |
BLAST software on the UPMEM architecture | Published (2016) | INRIA | Paper | Upon request |
Search
TITLE | STATUS | AUTHORS | PAPER/RESOURCE | CODE |
---|---|---|---|---|
Index Search | Completed | UPMEM / Private company | Upon request | GitHub |
Analytics & Database
Title | Status | Author | Paper/resource | Code |
---|---|---|---|---|
Design and Analysis of a Processing-in-DIMM Join Algorithm: A Case Study with UPMEM DIMMs | Paper accepted (SIGMOD 2023) | Yonsei University / Seoul National University | Coming soon | NA |
Adaptive Query Compilation with Processing-in-Memory | Published (HardBD 2023) | TU Ilmenau | Paper | NA |
Accelerating Large Table Scan using Processing-In-Memory Technology | Published (BTW 2023) | TU Ilmenau | Paper | GitHub |
PIM-tree: A Skew-resistant Index for Processing-in-Memory | Published (VLDB Endowment Volume 16 Issue 4 2022) | Carnegie Mellon University | Paper | GitHub |
Machine Learning / Deep Learning
Title | Status | Authors | Paper/resource | Code |
---|---|---|---|---|
An Experimental Evaluation of Machine Learning Training on a Real Processing-in-Memory System | Published (ISPASS 2023) | ETH Zurich | Paper | GitHub |
Implementation and Evaluation of Deep Neural Networks in Commercially Available Processing in Memory Hardware | Published (SOCC 2022) | Rochester Institute of Technology | Paper Thesis | NA |
An implementation of a deep learning recommendation model (DLRM) | On-going | University of British Columbia | On-going | GitHub |