arXiv subjects

Emanuele Venieri

Publications and source records attributed to Emanuele Venieri.

4 recordsLinked to original sources

arXiv2026

Is RISC-V Ready for Massively Parallel Astrophysical Codes?

We present a performance and portability evaluation of three well-established astrophysical production codes, namely iPIC3D, PLUTO, and OpenGadget3, on a Sophgo SG2044 RISC-V processor (part of the Monte Cimone cluster), with comparisons to AMD EPYC 9554 (x86) and NVIDIA GH200 Grace (ARM) systems. These applications represent memory-bound, compute-bound, and hybrid workloads, respectively. Numerical correctness is verified across all platforms, confirming portability. RISC-V shows consistently lower performance, with slowdowns of about $3-6\times$ relative to x86 and $5-9\times$ relative to ARM. The gap is mainly due to limited memory bandwidth, shared cache constraints, narrower 128-bit vector units, and lower clock frequency, but also less-mature auto-vectorization capability of the GNU compiler suite. Memory-bound kernels are the most affected, where early bandwidth saturation and L2 cache contention reduce scalability at higher thread counts. Hybrid MPI+OpenMP configurations reveal a trade-off between memory contention and communication overhead, with intermediate configurations achieving the best performance. These results suggest that RISC-V is capable of supporting scientific workloads; however, additional improvements in both hardware and compiler technology, particularly in auto-vectorization, are required to achieve competitive performance.

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arXiv2026

Monte Cimone v3: Where RISC-V Stands in High-Performance Computing

The Monte Cimone project provides a RISC-V testbed for High-Performacne Computing cluster. This paper presents Monte Cimone v3 (MCv3), the third iteration of the Monte Cimone RISC-V HPC cluster, integrating the SOPHGO Sophon SG2044 processor, an evolution of the SG2042 used in MCv2. We characterize MCv3 using HPL and STREAM benchmarks coupled with power measurements, and compare it against two reference platforms: the Intel Xeon Platinum 8480+(Sapphire Rapids) and the NVIDIA Grace CPU Superchip. Our results show that the SG2044 more than doubles single-core performance and improves scalability compared to SG2042. MCv3 achieves an energy efficiency of 3.08GFLOPs/W which improves of 10x w.r.t. MCv1 and is in the range of x86-64 and Arm servers. On pure performance when normalized on the SIMD/Vector length MCv3 on its peak efficiency point (16 cores) achieves 46% performance of Intel Sapphire Rapids server and 91% performance of NVIDIA Grace CPU superchip.

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arXiv2026

AME-PIM: Can Memory be Your Next Tensor Accelerator?

High Bandwidth Memory with Processing-in-Memory (HBM-PIM) offers an opportunity to reduce data movement by executing computation directly inside memory, but current commercial platforms expose limited instruction sets and require specialized software stacks. In this work, we investigate whether HBM-PIM can serve as a backend for ISA-level matrix acceleration, using the RISC-V Attached Matrix Extension (AME) as a semantic reference. We propose a PEP-based execution model that maps AME element-wise and matrix instructions to HBM-PIM micro-kernels and data instructions in memory operations. Differently from SoA HBM-PIM, we introduce a reduction-free outer-product dataflow that enables accumulation entirely within memory despite the lack of native reduction support. Our approach supports end-to-end execution of element-wise operations, GEMV, and GEMM in PIM mode, minimizing host involvement and off-chip transfers. An experimental evaluation on Samsung Aquabolt-XL shows that AME matrix tile multiplication achieves up to 14.9 GFLOP/s (59.4 FLOP/cycle) on a single HBM pseudo-channel.

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arXiv2025

Monte Cimone v2: Down the Road of RISC-V High-Performance Computers

Many RISC-V (RV) platforms and SoCs have been announced in recent years targeting the HPC sector, but only a few of them are commercially available and engineered to fit the HPC requirements. The Monte Cimone project targeted assessing their capabilities and maturity, aiming to make RISC-V a competitive choice when building a datacenter. Nowadays, Systems-on-chip (SoCs) featuring RV cores with vector extension, form factor and memory capacity suitable for HPC applications are available in the market, but it is unclear how compilers and open-source libraries can take advantage of its performance. In this paper, we describe the performance assessment of the upgrade of the Monte Cimone (MCv2) cluster with the Sophgo SG2042 processor on HPC workloads. Also adding an exploration of BLAS libraries optimization. The upgrade increases the attained node's performance by 127x on HPL DP FLOP/s and 69x on Stream Memory Bandwidth.

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