2024 Proceeding- General Chair:
- Kunal Agrawal,
- Program Chair:
- Erez Petrank
It is our great pleasure to welcome you to the 36th ACM Symposium on Parallelism in Algorithms and Architectures - SPAA 2024. SPAA aims to develop a deeper understanding of parallel and distributed computing, both in theory and in practice. Topics relevant to SPAA include algorithms, data structures, computational models, complexity theory, architectures, performance engineering, languages, runtime systems, compilers, programming systems, and networking systems. This year, there were 125 submissions to SPAA (117 regular submission and 8 brief announcements). The program committee accepted 35 regular papers and 19 brief announcements.
An Optimal MPC Algorithm for Subunit-Monge Matrix Multiplication, with Applications to LIS
We present an O(1)-round fully-scalable deterministic massively parallel algorithm for computing the min-plus matrix multiplication of unit-Monge matrices. We use this to derive a O(łog n)-round fully-scalable massively parallel algorithm for solving the ...
Distributed-Memory Randomized Algorithms for Sparse Tensor CP Decomposition
Candecomp / PARAFAC (CP) decomposition, a generalization of the matrix singular value decomposition to higher-dimensional tensors, is a popular tool for analyzing multidimensional sparse data. On tensors with billions of nonzero entries, computing a CP ...
Minimum Cost Loop Nests for Contraction of a Sparse Tensor with a Tensor Network
Sparse tensor decomposition and completion are common in numerous applications, ranging from machine learning to computational quantum chemistry. Typically, the main bottleneck in optimization of these models are contractions of a single large sparse ...
Tightening I/O Lower Bounds through the Hourglass Dependency Pattern
When designing an algorithm, one cares about arithmetic/computational complexity, but data movement (I/O) complexity plays an increasingly important role that highly impacts performance and energy consumption. For a given algorithm and a given I/O model, ...
A Framework for Parallelizing Approximate Gaussian Elimination
In a breakthrough result, Spielman and Teng (2004) developed a nearly-linear time solver for Laplacian linear equations, i.e. equations where the coefficient matrix is symmetric with non-negative diagonals and zero row sums. Since the development of the ...
Fault-Tolerant Parallel Integer Multiplication
Exascale machines have a small mean time between failures, necessitating fault tolerance. Out-of-the-box fault-tolerant solutions, such as checkpoint-restart and replication, apply to any algorithm but incur significant overhead costs. Long integer ...
