Future Students

I am always looking for motivated and hard-working students. Please apply to the ECE department at McMaster if you are interested in building compilers for scientific and machine learning applications. Please also email me your application and possibly (link to) your coding project samples. I strongly encourage applications from students that are a member of underrepresented groups to increase diversity in STEM.

Teaching

• COMP ENG 4SP4. High-Performance Programming. (Fall 2024)
• COMP ENG 3DY4. Computer Systems Integration Project. (Winter 2023, 2024)
• ECE 718: Special Topics in Computation, Compiler Design for High Performance Computing. (Fall 2023)
• CSC367: Parallel Programming. (Winter 2021)

Service

• Session Chair at Supercomputing'23, Program Committee member at IPDPS'23, Program Committee member at Supercomputing'23, External Review Committee at SPAA'22, Web Chair at PPoPP'22, Program Committee member at ICPP'22, Session Chair at ICPP'22, Reviewer at Journal of Supercomputing, ACM Transactions on Architecture and Code Optimization, and Journal of Parallel and Distributed Computing.

Major Awards

• Recieved Honorable Mention in the SIGHPC Doctoral Dissertation award for my PhD thesis . (2022)
• Recipient of ACM-IEEE CS George Michael Memorial HPC fellowship. (2020)
• First place in ACM student research competition grand finals across all ACM conferences. (2017)
• Recipient of Adobe fellowship. (2018)
• Recipient of Wolfond fellowship, computer science, University of Toronto. (2018)
• Best poster paper award in HPCS conference. (2018)


• First place in ACM CGO student research competition. (2017)
• German Academic Exchange Service (DAAD) to attend the University of Rostock, Germany. (2011)

Publications

• Runtime Composition of Iterations for Fusing Loop-carried Sparse Dependence
  Kazem Cheshmi, Michelle Mills Strout, and Maryam Mehri Dehnavi
  International Conference for High Performance Computing, Networking, Storage and Analysis, SC'23
  
  
• Register Tiling for Unstructured Sparsity in Neural Network Inference
  Lucas Wilkinson*, Kazem Cheshmi*, and Maryam Mehri Dehnavi (*Equal contributions)
  ACM SIGPLAN Conference on Programming Language Design and Implementation, PLDI'23 (Selected for MIT PL Review)
  
  
• Vectorizing Sparse Matrix Computations with Partially-Strided Codelets
  Kazem Cheshmi*, Zachary Cetinic*, and Maryam Mehri Dehnavi (*Equal contributions)
  International Conference for High Performance Computing, Networking, Storage and Analysis, SC'22
  
  
• HDagg: Hybrid Aggregation of Loop-carried Dependence Iterations in Sparse Matrix Computations
  Behrooz Zarebavani, Kazem Cheshmi, Bangtian Liu, Michelle Mills Strout, and Maryam Mehri Dehnavi
  IEEE International Parallel and Distributed Processing Symposium , IPDPS'22
  
  
• Optimizing Sparse Computations Jointly
  Kazem Cheshmi, Michelle Mills Strout, and Maryam Mehri Dehnavi
  Symposium on Principles and Practice of Parallel Programming , PPoPP'22
  
  
• NASOQ: Numerically Accurate Sparsity-Oriented QP Solver
  Kazem Cheshmi, Danny M. Kaufman, Shoaib Kamil, and Maryam Mehri Dehnavi
  ACM Transactions on Graphics , SIGGRAPH'20
  
  
• MatRox: Modular approach for improving data locality in Hierarchical (Mat)rix App(Rox)imation
  Bangtian Liu*, Kazem Cheshmi*, Saeed Soori, Michelle Mills Strout, Maryam Mehri Dehnavi (*Equal contributions)
  Symposium on Principles and Practice of Parallel Programming , PPoPP'20
  
  
• Sparse computation data dependence simplification for efficient compiler-generated inspectors
  Mahdi Soltan Mohammadi, Tomofumi Yuki, Kazem Cheshmi, Eddie C Davis, Mary Hall, Maryam Mehri Dehnavi, Payal Nandy, Catherine Olschanowsky, Anand Venkat, Michelle Mills Strout
  ACM SIGPLAN Conference on Programming Language Design and Implementation, PLDI'19



• ParSy: inspection and transformation of sparse matrix computations for parallelism
  Kazem Cheshmi, S. Kamil, Michelle Mills Strout, and Maryam Mehri Dehnavi
  International Conference for High Performance Computing, Networking, Storage and Analysis, SC'18.
  
  
• Extending index-array properties for data dependence analysis
  Mahdi Soltan Mohammadi, Kazem Cheshmi, Maryam Mehri Dehnavi, Anand Venkat, TomofumiYuki, and Michelle M. Strout
  International Workshop on Languages and Compilers for Parallel Computing, LCPC'18.
  
  
• Sparsity-aware storage format selection
  Kazem Cheshmi, Leila Cheshmi, and Maryam Mehri Dehnavi.
  International Conference on High Performance Computing & Simulation, HPCS'18 (Best paper poster award).
  
  
• Sympiler: Transforming Sparse Matrix Codes by Decoupling Symbolic Analysis
  Kazem Cheshmi, Shoaib Kamil, Michelle Mills Strout, and Maryam Mehri Dehnavi
  International Conference for High Performance Computing, Networking, Storage and Analysis, SC'17
  
  
• A clustered GALS Network-on-Chip architecture with communication-aware mapping
  Kazem Cheshmi, Siamak Mohammadi, Daniel Versick, Djamshid Tavangarian, and Jelena Trajkovic
  Euromicro International Conference on Parallel, Distributed and Network-Based Processing, PDP'15.
  
  
• Chameleon: Channel efficient optical network-on-chip
  Sebastien Le Beux, Hui Li, Ian O’Connor, Kazem Cheshmi, Xuchen Liu, Jelena Trajkovic, and Gabriela Nicolescu
  Design, Automation & Test in Europe Conference & Exhibition, DATE'14.
  
  
• Quota setting router architecture for quality of service in GALS network-on-chip
  Kazem Cheshmi, Jelena Trajkovic, Mohammadreza Soltaniyeh, and Siamak Mohammadi
  International Symposium on Rapid System Prototyping, RSP'13.
  
  

Open-Source

• Sympiler : is a domain-specific code-generator and library for sparse computation. It containts a set of techniques for loop tiling, splitting, fusion, and vectorization for sparse codes, such as sparse factorization and matrix multiplication.
  
  
• NASOQ : is a scalable and efficient Quadratic Programming solver that obtains solutions for requested accuracies.
  
  

“Capable is he who is wise - Happiness from wisdom will arise.” - Ferdowsi