Bioinformatics applications are one of the most relevant and compute-demanding applications today. While normally these applications are executed on clusters or dedicated parallel systems, in this work we explore the use of an alternative architecture. We focus on exploiting the compute-intensive characteristics offered by the graphics processors (GPU) in order to accelerate a bioinformatics application. The GPU is a good match for these applications as it is an inexpensive, highperformance SIMD architecture. In our initial experiments we evaluate the use of a regular graphics card to improve the performance of RAxML, a bioinformatics program for phylogenetic tree inference. In this paper we focus on porting to the GPU the most time-consuming loop, which accounts for nearly 50% of the total execution time. The preliminary results show that the loop code achieves a speedup of 3x while the whole application with a single loop optimization, achieves a speedup of 1.2x.

The initial use of 1,3-propanediol in mixed Mn/3d cluster chemistry has led to a Mn(III)(28)Mn(II)(8)Ni(II)(4) molecular aggregate which consists of two Mn(III)(8)Ni(2) loops and two Mn(III)(6)Mn(II)(4) supertetrahedral units and displays a high ground spin state value S(T) = 26 ± 1.

Graphics processors are designed to perform many floating-point operations per second. Consequently, they are an attractive architecture for high-performance computing at a low cost. Nevertheless, it is still not very clear how to exploit all their potential for general-purpose applications.In this work we present a comprehensive study of the performance of an application executing on the GPU. In addition, we analyze the possibility of using the graphics card to extend the life-time of a computer system.In our experiments we compare the execution on a midclass GPU (NVIDIA GeForce FX 5700LE) with a high-end CPU (Pentium 4 3.2GHz). The results show that to achieve high speedup with the GPU you need to: (1) format the vectors into two-dimensional arrays;(2) process large data arrays; and (3) perform a considerable amount of operations per data element. Finally, we study the performance when upgrading a low-end system by simply adding a GPU. This solution is cheaper, results in smaller power consumption and achieves higher speedup (8.1x versus 1.3x) than a full upgrade to a new high-end system.

Two molecular grid-like clusters are reported, one is a discrete [3 × 5] grid and the other a [3 × 4] grid within a Mn12Ni2 loop. Both Mn24Ni2 and Mn15 aggregates display novel and aesthetically pleasing structures with the former one being among the highest nuclearity heterometallic MnxMy clusters (M = any transition metal ion).

We report the synthesis, crystal structures and magnetic properties of the giant heterometallic [Mn36Ni4]2−/0 (compounds 1, 2)/[Mn32Co8] (compound 3) “loops-of-loops-and-supertetrahedra” molecular aggregates and of a [Mn2Ni6]2+ compound (cation of 4) that is structurally related with the cation co-crystallizing with the anion of 1. In particular, after the initial preparation and characterization of compound [Mn2Ni6(μ4-O)2(μ3-OH)3(μ3-Cl)3(O2CCH3)6(py)8]2+[Mn36Ni4(μ4-O)8(μ3-O)4(μ3-Cl)8Cl4(O2CCH3)26(pd)24(py)4]2− (1) we targeted the isolation of (i) both the cationic and the anionic aggregates of 1 in a discrete form and (ii) the Mn/Co analog of [Mn36Ni4]2− aggregate. Our synthetic efforts toward these directions afforded the discrete [Mn36Ni4] “loops-of-loops-and-supertetrahedra” aggregate [Mn36Ni4(μ4-O)8(μ3-O)4(μ3-Cl)8Cl2(O2CCH3)26(pd)24(py)4(H2O)2] (2), the heterometallic Mn/Co analog [Mn32Co8(μ4-O)8(μ3-O)4(μ3-Cl)8Cl2(μ2-OCH2CH3)2(O2CCH3)28(pd)22(py)6] (3) and the discrete [Mn2Ni6]2+ cation [Mn2Ni6(μ4-O)2(μ3-OH)4(μ3-Cl)2(O2CCH3)6(py)8](ClO4)(OH) (4). The structure of 1 consists of a mixed valence [Mn28IIIMn8IINi4II]2− molecular aggregate that contains two Mn8IIINi2II loops separated by two Mn6IIIMn4II supertetrahedral units and a [Mn2IIINi6II]2+ cation based on two [MnIIINi3II(μ4-O)(μ3-OH)1.5(μ3-Cl)1.5]4+ cubane sub-units connected through both mono- and tri-atomic bridges provided by the μ4-O2− and carboxylate anions. The structures of 2–4 are related to those of the compounds co-crystallized in 1 exhibiting however some differences that shall be discussed in detail in the manuscript. Magnetism studies revealed the presence of dominant ferromagnetic interactions in 1–3 that lead to large ground state spin (ST) values for the “loops-of-loops-and-supertetrahedra” aggregates and antiferromagnetic exchange interactions in 4 that lead to a low (and possibly zero) ST value. In particular, dc and ac magnetic susceptibility studies revealed that the discrete [Mn36Ni4] aggregate exhibits a large ST value ~ 26 but is not a new SMM. The ac magnetic susceptibility studies of the [Mn32Co8] analog revealed an extremely weak beginning of an out-of-phase tail indicating the presence of a very small relaxation barrier assignable to the anisotropic Co2+ions and a resulting out-of-phase ac signal whose peak is at very low T.